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Thursday, 04 January 2018 16:13

LLNL Researchers Improve Nanoscale 3D Printing

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Lawrence Livermore National Laboratory (LLNL) researchers have discovered novel ways to extend the capabilities of two-photon lithography (TPL), a high-resolution 3D printing technique capable of producing nanoscale features smaller than one-hundredth the width of a human hair.

The findings, recently published on the cover of the journal ACS Applied Materials & Interfaces, also unleashes the potential for X-ray computed tomography (CT) to analyze stress or defects noninvasively in embedded 3D-printed medical devices or implants.

Two-photon lithography typically requires a thin glass slide, a lens and an immersion oil to help the laser light focus to a fine point where curing and printing occurs. It differs from other 3D-printing methods in resolution, because it can produce features smaller than the laser light spot, a scale no other printing process can match. The technique bypasses the usual diffraction limit of other methods because the photoresist material that cures and hardens to create structures — previously a trade secret — simultaneously absorbs two photons instead of one.

In the paper, LLNL researchers describe cracking the code on resist materials optimized for two-photon lithography and forming 3D microstructures with features less than 150 nanometers. Previous techniques built structures from the ground up, limiting the height of objects because the distance between the glass slide and lens is usually 200 microns or less. By turning the process on its head — putting the resist material directly on the lens and focusing the laser through the resist — researchers can now print objects multiple millimeters in height. Furthermore, researchers were able to tune and increase the amount of X-rays the photopolymer resists could absorb, improving attenuation by more than 10 times over the photoresists commonly used for the technique.

“In this paper, we have unlocked the secrets to making custom materials on two-photon lithography systems without losing resolution,” said LLNL researcher James Oakdale, a co-author on the paper.

Because the laser light refracts as it passes through the photoresist material, the linchpin to solving the puzzle, the researchers said, was “index matching” – discovering how to match the refractive index of the resist material to the immersion medium of the lens so the laser could pass through unimpeded. Index matching opens the possibility of printing larger parts, they said, with features as small as 100 nanometers.

“Most researchers who want to use two-photon lithography for printing functional 3D structures want parts taller than 100 microns,” said Sourabh Saha, the paper’s lead author. “With these index-matched resists, you can print structures as tall as you want. The only limitation is the speed. It’s a tradeoff, but now that we know how to do this, we can diagnose and improve the process.”

By tuning the material’s X-ray absorption, researchers can now use X-ray-computed tomography as a diagnostic tool to image the inside of parts without cutting them open or to investigate 3D-printed objects embedded inside the body, such as stents, joint replacements or bone scaffolds. These techniques also could be used to produce and probe the internal structure of targets for the National Ignition Facility, as well as optical and mechanical metamaterials and 3D-printed electrochemical batteries. 

The only limiting factor is the time it takes to build, so researchers will next look to parallelize and speed up the process. They intend to move into even smaller features and add more functionality in the future, using the technique to build real, mission-critical parts.

“It’s a very small piece of the puzzle that we solved, but we are much more confident in our abilities to start playing in this field now,” Saha said. “We’re on a path where we know we have a potential solution for different types of applications. Our push for smaller and smaller features in larger and larger structures is bringing us closer to the forefront of scientific research that the rest of the world is doing. And on the application side, we’re developing new practical ways of printing things.”

The work was funded through the Laboratory Directed Research and Development (LDRD) program. Other LLNL researchers who contributed to the project include Jefferson Cuadra, Chuck Divin, Jianchao Ye, Jean-Baptiste Forien, Leonardus Bayu Aji, Juergen Biener and Will Smith.

Researchers from Lawrence Livermore National Laboratory (LLNL) and Autodesk are joining forces to explore how design software can accelerate innovation for three-dimensional printing of advanced materials.

Under an 18-month Cooperative Research and Development Agreement (CRADA), LLNL will use state-of-the-art software for generative design from San Rafael-based Autodesk Inc. as it studies how new material microstructures, arranged in complex configurations and printed with additive manufacturing techniques, will produce objects with physical properties that were never before possible.

In the project, LLNL researchers will bring to bear several key technologies, such as additive manufacturing, material modeling and architected design (arranging materials at the micro and nanoscale through computational design).

LLNL and Autodesk have selected next-generation protective helmets as a test case for their technology collaboration, studying how to improve design performance.

“As an organization that is pushing the limits on generative design and high-performance computing, Autodesk is an ideal collaborator as we investigate next-generation manufacturing,” said Anantha Krishnan, LLNL’s associate director for engineering.

“With its extensive cross-industry customer base, Autodesk can help us examine how our foundational research in architected materials and new additive manufacturing technology might transfer into a variety of domains.”

Mark Davis, Autodesk’s senior director of design research, called helmet design an excellent example of a design problem with multiple objectives, such as the constraints of desired weight, cost, durability, material thickness and response to compression.

“Giving the software goals and constraints as input, then allowing the computer to synthesize form and optimize across multiple materials, will lead to the discovery of unexpected, high-performing designs that would not have otherwise been pursued,” Davis added.

Patrick Dempsey, LLNL’s director of strategic engagements, noted: “Livermore is excited about combining its knowledge in materials and microstructures with the capabilities of a global leader in design software to demonstrate the ability of additive manufacturing to create new products.”

Through the application of goal-oriented design software tools, LLNL and Autodesk expect to generate and analyze the performance of very large sets – thousands to tens of thousands – of different structural configurations of material microarchitectures.

In addition to benefiting from the use of computer software, helmet design also stands to receive considerable advantages from additive manufacturing.

Helmets represent a class of objects whose internal structures not only need to be lightweight, but also must absorb impact and dissipate energy predictably.

Advanced additive manufacturing techniques are expected to allow the LLNL/Autodesk researchers to produce complex material microstructures that will dissipate energy better than what is currently possible with traditionally manufactured helmet pads such as foams and pads.

LLNL’s Eric Duoss, a materials engineer and the co-principal investigator for the CRADA with Lab computational engineer Dan White, believes the agreement could lead to new design methodologies with helmets as just one example.

“The difference in the design method we are proposing versus historically is that many of the previous manufacturing constraints can be eliminated,” Duoss said.

“Additive manufacturing provides the opportunity for unprecedented breakthroughs in new structures and new material properties for a wide range of applications,” Duoss added.

It has yet to be determined what kinds of helmets will be designed under the CRADA, but sports helmets, including football, baseball, biking and skiing, are possible, according to Duoss.

“One of the important things we hope to gain from this CRADA is to know what a great helmet design looks like, and we aim to build and test components of those helmet designs,” he said.

Within the past two years, the Lab’s Additive Manufacturing Initiative team has used 3D printing to produce ultralight and ultrastiff mechanical materials that don’t exist in nature, produced mechanical energy absorbing materials and printed graphene aerogels.

Francesco Lorio, primary investigator on the Autodesk team and a computational science expert, explains: "By combining the advanced additive manufacturing techniques at LLNL with our ability to compute shapes made of complex combinations of materials, we stand to find breakthrough designs for the helmet.” His team envisions a future where any product can be composed of bespoke materials “appropriately distributed at the micro and macro scale to optimally satisfy a desired function.”

Other LLNL staffers working on the project are: computational engineers Nathan Barton, Mark Messner and Todd Weisgraber; chemical engineer Tom Wilson, materials engineer Tim Ford, chemist Jeremy Lenhardt, applied physicist Willy Moss and mechanical engineer Michael King.

The Lab’s Additive Manufacturing Initiative team is developing new approaches to integrating design, fabrication and certification of advanced materials.

Using high-performance computing, new materials are modeled virtually and then optimized computationally. The Lab is simultaneously advancing the science of additive manufacturing and materials science, as demonstrated by its work in micro-architected metamaterials – artificial materials with properties not found in nature.

Friday, 24 April 2015 11:59

3D Printed Graphene Aerogels

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A new type of graphene aerogel will make for better energy storage, sensors, nanoelectronics, catalysis and separations.

Lawrence Livermore National Laboratory researchers have made graphene aerogel microlattices with an engineered architecture via a 3D printing technique known as direct ink writing. The research appears in the April 22 edition of the journal, Nature Communications.

The 3D printed graphene aerogels have high surface area, excellent electrical conductivity, are lightweight, have mechanical stiffness and exhibit supercompressibility (up to 90 percent compressive strain). In addition, the 3D printed graphene aerogel microlattices show an order of magnitude improvement over bulk graphene materials and much better mass transport.

Aerogel is a synthetic porous, ultralight material derived from a gel, in which the liquid component of the gel has been replaced with a gas. It is often referred to as “liquid smoke.”

Previous attempts at creating bulk graphene aerogels produced a largely random pore structure, excluding the ability to tailor transport and other mechanical properties of the material for specific applications such as separations, flow batteries and pressure sensors.

“Making graphene aerogels with tailored macro-architectures for specific applications with a controllable and scalable assembly method remains a significant challenge that we were able to tackle,” said engineer Marcus Worsley, a co-author of the paper. “3D printing allows one to intelligently design the pore structure of the aerogel, permitting control over mass transport (aerogels typically require high pressure gradients to drive mass transport through them due to small, tortuous pore structure) and optimization of physical properties, such as stiffness. This development should open up the design space for using aerogels in novel and creative applications.”

During the process, the graphene oxide (GO) inks are prepared by combining an aqueous GO suspension and silica filler to form a homogenous, highly viscous ink. These GO inks are then loaded into a syringe barrel and extruded through a micronozzle to pattern 3D structures.

“Adapting the 3D printing technique to aerogels makes it possible to fabricate countless complex aerogel architectures for applications such as mechanical properties and compressibility, which has never been achieved before, ” said engineer Cheng Zhu, the other co-author of the journal article.

Other Livermore researchers include Yong-Jin Han, Eric Duoss, Alexandra Golobic, Joshua Kuntz and Christopher Spadaccini. The work is funded by the Laboratory Directed Research and Development Program.

For more information, visit: www.llnl.gov

Lawrence Livermore National Laboratory researchers have developed an efficient method to measure residual stress in metal parts produced by powder-bed fusion additive manufacturing.

This 3D printing process produces metal parts layer by layer using a high-energy laser beam to fuse metal powder particles. When each layer is complete, the build platform moves downward by the thickness of one layer, and a new powder layer is spread on the previous layer.

While this process is able to produce quality parts and components, residual stress is a major problem during the fabrication process. That’s because large temperature changes near the last melt spot -- rapid heating and cooling -- and the repetition of this process result in localized expansion and contraction, factors that cause residual stress.

Aside from their potential impact on mechanical performance and structural integrity, residual stress may cause distortions during processing resulting in a loss of net shape, detachment from support structures and, potentially, the failure of additively manufactured (AM) parts and components.

An LLNL research team, led by engineer Amanda Wu, has developed an accurate residual stress measurement method that combines traditional stress-relieving methods (destructive analysis) with modern technology: digital image correlation (DIC). This process is able to provide fast and accurate measurements of surface-level residual stresses in AM parts.

The team used DIC to produce a set of quantified residual stress data for AM, exploring laser parameters. DIC is a cost-effective, image analysis method in which a dual camera setup is used to photograph an AM part once before it’s removed from the build plate for analysis and once after. The part is imaged, removed and then re-imaged to measure the external residual stress.

In a part with no residual stresses, the two sections should fit together perfectly and no surface distortion will occur. In AM parts, residual stresses cause the parts to distort close to the cut interface. The deformation is measured by digitally comparing images of the parts or components before and after removal. A black and white speckle pattern is applied to the AM parts so that the images can be fed into a software program that produces digital illustrations of high to low distortion areas on the part’s surface.

In order to validate their results from DIC, the team collaborated with Los Alamos National Laboratory (LANL) to perform residual stress tests using a method known as neutron diffraction (ND). This technique, performed by LANL researcher Donald Brown, measures residual stresses deep within a material by detecting the diffraction of an incident neutron beam. The diffracted beam of neutrons enables the detection of changes in atomic lattice spacing due to stress.

Although it’s highly accurate, ND is rarely used to measure residual stress because there are only three federal research labs in the U.S. -- LANL being one of them -- that have the high-energy neutron source required for this analysis.

The LLNL team’s DIC results were validated by the ND experiments, showing that DIC is a reliable way to measure residual stress in powder-bed fusion AM parts.

Their findings were the first to provide quantitative data showing internal residual stress distributions in AM parts as a function of laser power and speed. The team demonstrated that reducing the laser scan vector length instead of using a continuous laser scan regulates temperature changes during processing to reduce residual stress. Furthermore, the results show that rotating the laser scan vector relative to the AM part’s largest dimension also helps reduce residual stress. The team’s results confirm qualitative data from other researchers that reached the same conclusion.

By using DIC, the team was able to produce reliable quantitative data that will enable AM researchers to optimally calibrate process parameters to reduce residual stress during fabrication. Laser settings (power and speed) and scanning parameters (pattern, orientation angle and overlaps) can be adjusted to produce more reliable parts. Furthermore, DIC allowed the Lawrence Livermore team to evaluate the coupled effects of laser power and speed, and to observe a potentially beneficial effect of subsurface layer heating on residual stress development.

“We took time to do a systematic study of residual stresses that allowed us to measure things that were not quantified before,” Wu said. “Being able to calibrate our AM parameters for residual stress minimization is critical.”

LLNL’s findings eventually will be used to help qualify properties of metal parts built using the powder-bed fusion AM process. The team’s research helps build on other qualification processes designed at LLNL to improve quality and performance of 3D printed parts and components.

Wu and her colleagues are part of LLNL’s Accelerated Certification of Additively Manufactured Metals (ACAMM) Strategic Initiative. The other members of the Lawrence Livermore team include Wayne King, Gilbert Gallegos and Mukul Kumar.

The team’s results were reported in an article titled “An Experimental Investigation Into Additive Manufacturing-Induced Residual Stresses in 316L Stainless Steel” that was recently published in the journal, Metallurgical and Materials Transactions.

For more information, visit: acamm.llnl.gov

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