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Category: 3D printing – Page 30

Flexible electronics have enabled the design of sensors, actuators, microfluidics and electronics on flexible, conformal and/or stretchable sublayers for wearable, implantable or ingestible applications. However, these devices have very different mechanical and biological properties when compared to human tissue and thus cannot be integrated with the human body.

A team of researchers at Texas A&M University has developed a new class of biomaterial inks that mimic native characteristics of highly conductive , much like skin, which are essential for the ink to be used in 3D printing.

This biomaterial ink leverages a new class of 2D nanomaterials known as molybdenum disulfide (MoS2). The thin-layered structure of MoS2 contains defect centers to make it chemically active and, combined with modified gelatin to obtain a flexible hydrogel, comparable to the structure of Jell-O.

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Engineers have created intelligent 3D printers that can quickly detect and correct errors, even in previously unseen designs, or unfamiliar materials like ketchup and mayonnaise, by learning from the experiences of other machines.

The engineers, from the University of Cambridge, developed a machine learning algorithm that can detect and correct a wide variety of different errors in real time, and can be easily added to new or existing machines to enhance their capabilities. 3D printers using the algorithm could also learn how to print new materials by themselves. Details of their low-cost approach are reported in the journal Nature Communications.

3D has the potential to revolutionize the production of complex and customized parts, such as aircraft components, personalized medical implants, or even intricate sweets, and could also transform manufacturing supply chains. However, it is also vulnerable to production errors, from small-scale inaccuracies and mechanical weaknesses through to total build failures.

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MIT researchers have developed a method for 3D printing materials with tunable mechanical properties, which can sense how they are moving and interacting with the environment. The researchers create these sensing structures using just one material and a single run on a 3D printer.

To accomplish this, the researchers began with 3D-printed lattice materials and incorporated networks of air-filled channels into the structure during the . By measuring how the pressure changes within these channels when the structure is squeezed, bent, or stretched, engineers can receive feedback on how the material is moving.

These lattice materials are composed of in a repeating pattern. Changing the size or shape of the cells alters the material’s mechanical properties, such as stiffness or hardness. For instance, a denser network of cells makes a stiffer structure.

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3D printed material:

MIT researchers manufactured objects made of flexible plastic and electrically conductive filaments. Some varieties of 3D-printed objects can now feel, using a new technique that builds sensors directly into their materials. 3D printing can be considered printing, although not as it’s traditionally been defined. The method opens opportunities for embedding sensors within architected materials, a class of materials whose mechanical properties are programmed through form and composition.

The researchers also created 3D editing software, known as MetaSense, to help users build interactive devices using these metamaterials. The new technique 3D-prints objects made from metamaterial substances made of grids of repeating cells. It was designed to conform to a person’s hand. When a user squeezes one of the flexible buttons, the resulting electric signals help control a digital synthesizer.

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MIT researchers have developed a method for 3D printing materials with tunable mechanical properties, that sense how they are moving and interacting with the environment. The researchers create these sensing structures using just one material and a single run on a 3D printer.

To accomplish this, the researchers began with 3D-printed lattice materials and incorporated networks of air-filled channels into the structure during the printing process. By measuring how the pressure changes within these channels when the structure is squeezed, bent, or stretched, engineers can receive feedback on how the material is moving.

The method opens opportunities for embedding sensors within architected materials, a class of materials whose mechanical properties are programmed through form and composition. Controlling the geometry of features in architected materials alters their mechanical properties, such as stiffness or toughness. For instance, in cellular structures like the lattices the researchers print, a denser network of cells makes a stiffer structure.

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It’s “a revolutionary scientific advance in molecular data storage and cryptography.”

Scientists from the University of Texas at Austin sent a letter to colleagues in Massachusetts with a secret message: an encryption key to unlock a text file of L. Frank Baum’s classic novel The Wonderful Wizard of Oz. The twist: The encryption key was hidden in a special ink laced with polymers, They described their work in a recent paper published in the journal ACS Central Science.

When it comes to alternative means for data storage and retrieval, the goal is to store data in the smallest amount of space in a durable and readable format. Among polymers, DNA has long been the front runner in that regard. As we’ve reported previously, DNA has four chemical building blocks—adenine (A), thymine (T), guanine (G), and cytosine ©—which constitute a type of code. Information can be stored in DNA by converting the data from binary code to a base-4 code and assigning it one of the four letters. A single gram of DNA can represent nearly 1 billion terabytes (1 zettabyte) of data. And the stored data can be preserved for long periods—decades, or even centuries.

There have been some inventive twists on the basic method for DNA storage in recent years. For instance, in 2019, scientists successfully fabricated a 3D-printed version of the Stanford bunny—a common test model in 3D computer graphics—that stored the printing instructions to reproduce the bunny. The bunny holds about 100 kilobytes of data, thanks to the addition of DNA-containing nanobeads to the plastic used to 3D print it. And scientists at the University of Washington recently recorded K-Pop lyrics directly onto living cells using a “DNA typewriter.”

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In a world where 3D printing is being applied to everything from houses to rockets to guns 0, the question comes up as to where manufacturing might be headed next.

A new device, called LeviPrint, adds a unique feature to the manufacturing process: acoustic levitation. By trapping small objects in high frequency sound waves, LeviPrint can be used to build a variety of different structures without touching any of the pieces.

In a video released by researchers from Spain’s Universidad Publica de Navarra, or UPNA, LeviPrint can be seen building a variety of different things, including a bridge, a hoop made out of liquid glue droplets and a cat’s ears.

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Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out how to print with these materials can be a complex, costly conundrum.

Often, an expert operator must use manual trial-and-error—possibly making thousands of prints—to determine ideal parameters that consistently print a new material effectively. These parameters include speed and how much material the printer deposits.

MIT researchers have now used artificial intelligence to streamline this procedure. They developed a machine-learning system that uses to watch the and then correct errors in how it handles the material in real-time.

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