Chronic organ failure is a major cause of death – around 500,000 people are diagnosed with heart failure every year in the U.S. And yet, only a few thousand heart transplants are performed annually. Most people just aren't good candidates because of their age or condition and the scarcity of donor organs.At Stanford, I’ve spent the last five years pursuing a science fiction dream: What if we could 3D print new hearts and other organs on demand, using cells from a patient’s own body? How do we take a few cells in a petri dish and turn them into a kilogram of tissue that you can watch with your own eyes beating?There’s a lot of very hard challenges associated with scaling-up in biology. How do you make billions of cells affordably, reliably, and reproducibly? How do you print them quickly, mature them, let them thrive? We have to vascularize and feed the cells, put blood vessels into the tissues, so we can provide them the oxygen and nutrients they need to survive.In three and a half years, my lab plans to have a 3D-printed human organ inside a pig model. We hope that large animal study becomes a springboard to then lay out the milestones needed for a first in-human trial. That will likely be more than a decade away. There’s a lot of work to be done, but there are real forward steps that we're taking.The dream outcome is that we get a bioprinted heart in a human. With xenotransplants from pigs, you still need to be on a very high dose of immunosuppressants, and even then, it usually gets rejected after a month or two. Our goal would be to make your own heart, made of your own cells, on demand, with no need for immunosuppression. It really is the holy grail of what I think curative medicine ought to move towards: You’ve got a failing organ? Here’s a new one.I present this work to venture capitalists sometimes, and I talk to business people, and the response I get is that we’re being too ambitious. And to me, that means we’re doing academia right.I present this work to venture capitalists sometimes, and I talk to business people, and the response I get is that we’re being too ambitious. And to me, that means we’re doing academia right.”The private sector will fund what it’s willing to, which is five or 10 years in the future. When you’re really trying to do something different, train up a new workforce with a new set of skills, create new paradigms, that’s the role of academia. That’s our job. And it’s a privilege and an extremely exciting place to work. I just love my job, and I’m very grateful for the opportunity to take a problem that is impossible and make it not quite impossible.

Stanford bioengineer Mark Skylar-Scott on his “science fiction” quest to 3D print human hearts and other organs on demand, using cells from a patient’s own body.

'It really is the holy grail of curative medicine'

Ghost Dance is a research project out of Lusófona University that sets out to explore the value of human connection and how it can be recreated with a virtual dance partner. Project directors Cecilia de Lima and Rui Antunes looked to inertial motion capture to create fluid motions that real-life dancers could perform alongside. Challenge: The Ghost Dance team needed to build a 3D model based on dancers' movements to test the relationship between virtual and real-life performers. Creating a realistic model posed a significant challenge. Solution: Inertial motion capture technology allowed dancers to record an entire routine with maximum comfort and accuracy. The result was a virtual partner with smooth motions, making for a natural performance with its real-life counterpart.Key takeaways <ul><li>A diverse range of motion: Even complex movements in contemporary dance can be tracked with inertial sensors</li><li>Efficient recording: Entire choreographed performances were recorded quickly, to work around time restrictions in the dance studio</li><li>Comfortable wear: Dancers could perform unobstructed thanks to the adjustable nature of Xsens wearable technology</li><li>Fluid results: The virtual dance partner moved smoothly, creating a high sense of realism during the performance</li></ul>Studying the importance of human touchBefore beginning the project, the <a href="https://ghostdance.ulusofona.pt/outcomes/publications" target="_blank" rel="noopener noreferrer">Ghost Dance</a> directors had two main goals. “The first was to understand the need for physical, bodily presence between humans,” says Rui Antunes, Director. “In the new era of technology, we seem to be growing further apart, and we wanted to see whether this had an impact on our wellbeing.” To explore this, the team planned to use VR goggles to compare dancing with a human partner and a virtual counterpart. “We wanted to find out what happens when a human body interacts with a virtual entity,” explains Cecilia de Lima, Director. “We knew it would make for a completely different experience, but we needed to find out how and why.” The other part of Cecilia and Rui’s project was to see if virtual dance partners could improve via machine learning. The digital counterparts were created from the dancer’s movements, but they wanted to see if they could develop their own routines based on the information provided.To achieve these goals, extensive planning was put into place to find the right technology.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888563673-Ghost+dance+Performance+Dancing+a+duet+with+avatar+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Building a virtual dance partner This complex project required not only a skilled team, but a set of specialized technology to record the dancers’ performances and transform them into a digital counterpart.Dancers use movements that aren’t typical in day-to-day life, so it was crucial to have a motion capture system to accommodate that complexity. “The Xsens system could accurately record their movements for a perfect translation into a 3D model,” says Rui. Inertial sensors contain accelerometers and gyroscopes, tracking the joint rotation and velocity of the subject. This pinpoint precision allowed for lifelike movements in the virtual dance partner, making a more natural experience for the real-life dancers.“Comfort is essential when dancing,” explains Cecilia. “We needed the motion capture technology to be unobtrusive to get the best results.” The system consists of 17 sensors, which all strap individually onto the body, making each one adjustable to the wearer’s preferences. Having this comfort led to more natural, fluid moves to create the virtual partner. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888595821-Ghost+dance+Motion+Capture+for+Avatar+Dance+duets+7.jpg" style="width:100%px" class="fr-fic fr-dib" />Machine learning for virtual dance partnersAfter the dancers were recorded and the virtual partners were made, Cecilia and Rui needed to see whether they could develop from the base-level data. To do this, they created machine-learning algorithms to put the models to the test.A machine cannot make subjective decisions, so the team found a solution to objectify and quantify the dancers’ movements. “The eight Laban efforts are commonly used in theatre and dance classes to expand students’ creativity,” says Cecilia. “These are basic movements, including punching, wringing, and pressing, that a robot could easily identify.”From this information, Cecilia and Rui hope to develop a virtual dance partner that can make its own organic moves in time with a real-life dancer. “Inertial motion capture was the perfect choice for this type of research,” continues Rui. “We had a well-built model that was based on real movement, which provided a baseline for machine learning.”“The research project was incredibly enlightening on the importance of human connection,” concludes Cecilia. “Virtual dance partners are not currently able to replace real ones.” Small sensations, such as breaths and footsteps, are vital when dancing cohesively with a partner. At this stage of technology development, these nuances are not available digitally. However, that’s not to say it won’t happen in the future. Ghost Dance proved that in the future, this could be a feasible alternative to dancing with a real counterpart. It seems increasingly possible when using inertial motion capture to create the basis of the digital partner.Using Xsens meant that the dancers could perform freely, with no need to adjust choreography. This led to an optimal experience when dancing with a virtual partner. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888642787-Ghost+dance+Overlay+of+virtual+and+real+partners+dancing+3.png" style="width:100%px" class="fr-fic fr-dib" />

With Inertial Motion Capture

Ghost Dance: Building a virtual dance partner

One year after Unitree H1 (1.8m) pioneered the first standing backflip by an electric humanoid robot (March 2024). Meet the Unitree G1 – now flawlessly conquering an even more challenging standing side flip. (Zero malfunctions/damage occurred during programming and filming.)

One year after Unitree H1 (1.8m) pioneered the first standing backflip by an electric humanoid robot (March 2024). Meet the Unitree G1 – now flawlessly conquering an even more challenging standing side flip. (Zero malfunctions/damage occurred during programming and filming.)

World's First Side-Flipping Humanoid Robot: Unitree G1

It’s difficult to build devices that replicate the fluid, precise motion of humans, but that might change if we could pull a few (literal) strings.At least, that’s the idea behind “cable-driven” mechanisms in which running a string through an object generates streamlined movement across an object’s different parts. Take a robotic finger, for example: You could embed a cable through the palm to the fingertip of this object and then pull it to create a curling motion.While cable-driven mechanisms can create real-time motion to make an object bend, twist, or fold, they can be complicated and time-consuming to assemble by hand. To automate the process, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed an all-in-one 3D printing approach called “Xstrings.” Part design tool, part fabrication method, Xstrings can embed all the pieces together and produce a cable-driven device, saving time when assembling bionic robots, creating art installations, or working on dynamic fashion designs.3D printing approach strings together cable-driven mechanisms for you Video: MIT CSAILIn a <a href="https://groups.csail.mit.edu/hcie/files/research-projects/xstrings/xstrings.pdf" target="_blank">paper</a> to be presented at the 2025 Conference on Human Factors in Computing Systems (CHI2025), the researchers used Xstrings to print a range of colorful and unique objects that included a red walking lizard robot, a purple wall sculpture that can open and close like a peacock’s tail, a white tentacle that curls around items, and a white claw that can ball up into a fist to grab objects.To fabricate these eye-catching mechanisms, Xstrings allows users to fully customize their designs in a software program, sending them to a multi-material 3D printer to bring that creation to life. You can automatically print all the device’s parts in their desired locations in one step, including the cables running through it and the joints that enable its intended motion.MIT CSAIL postdoc and lead author Jiaji Li says that Xstrings can save engineers time and energy, reducing 40 percent of total production time compared to doing things manually. “Our innovative method can help anyone design and fabricate cable-driven products with a desktop bi-material 3D printer,” says Li.<h2>A new twist on cable-driven fabrication</h2>To use the Xstrings program, users first input a design with specific dimensions, like a rectangular cube divided into smaller pieces with a hole in the middle of each one. You can then choose which way its parts move by selecting different “primitives:” bending, coiling (like a spring), twisting (like a screw), or compressing — and the angle of these motions.For even more elaborate creations, users can incorporate multiple primitives to create intriguing combinations of motions. If you wanted to make a toy snake, you could include several twists to create a “series” combo, in which a single cord drives a sequence of motions. To create the robot claw, the team embedded multiple cables into a “parallel” combination, where several strings are embedded, to enable each finger to close up into a fist.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742432637463-mit-Xstrings-diagram.png" style="width:100%px" class="fr-fic fr-dib" />Xstrings facilitates how cables are integrated into the object it’s producing. Users can choose exactly how the strings are secured, including its endpoint, the holes within the structure that the cord passes through, and where you’d pull to operate the device.  Image courtesy of the researchers.Beyond fine-tuning the way cable-driven mechanisms move, Xstrings also facilitates how cables are integrated into the object. Users can choose exactly how the strings are secured, in terms of where the “anchor” (endpoint), “threaded areas” (or holes within the structure that the cord passes through), and “exposed point” (where you’d pull to operate the device) are located. With a robot finger, for instance, you could choose the anchor to be located at the fingertip, with a cable running through the finger and a pull tag exposed at the other end.Xstrings also supports diverse joint designs by automatically placing components that are elastic, compliant, or mechanical. This allows the cable to turn as needed as it completes the device’s intended motion.<h2>Driving unique designs across robotics, art, and beyond</h2>Once users have simulated their digital blueprint for a cable-driven item, they can bring it to life via fabrication. Xstrings can send your design to a fused deposition modeling 3D printer, where plastic is melted down into a nozzle before the filaments are poured out to build structures up layer by layer.Xstrings uses this technique to lay out cables horizontally and build around them. To ensure their method would successfully print cable-driven mechanisms, the researchers carefully tested their materials and printing conditions.For example, the researchers found that their strings only broke after being pulled up and down by a mechanical device more than 60,000 times. In another test, the team discovered that printing at 260 degrees Celsius with a speed of 10-20 millimeters per second was ideal for producing their many creative items.“The Xstrings software can bring a variety of ideas to life,” says Li. “It enables you to produce a bionic robot device like a human hand, mimicking our own gripping capabilities. You can also create interactive art pieces, like a cable-driven sculpture with unique geometries, and clothes with adjustable flaps. One day, this technology could enable the rapid, one-step creation of cable-driven robots in outer space, even within highly confined environments such as space stations or extraterrestrial bases.”The team’s approach offers plenty of flexibility and a noticeable speed boost to fabricating cable-driven objects. It creates objects that are rigid on the outside, but soft and flexible on the inside; in the future, they may look to develop objects that are soft externally but rigid internally, much like humans’ skin and bones. They’re also considering using more resilient cables, and, instead of just printing strings horizontally, embedding ones that are angled or even vertical.Li wrote the paper with Zhejiang University master’s student Shuyue Feng; Tsinghua University master’s student Yujia Liu; Zhejiang University assistant professor and former MIT Media Lab visiting researcher Guanyun Wang; and three CSAIL members: Maxine Perroni-Scharf, an MIT PhD student in electrical engineering and computer science; Emily Guan, a visiting researcher; and senior author Stefanie Mueller, the TIBCO Career Development Associate Professor in the MIT departments of Electrical Engineering and Computer Science and Mechanical Engineering, and leader of the HCI Engineering Group.

The “Xstrings” method can produce a range of colorful and unique objects, like a white tentacle that curls around items and a purple wall sculpture that can open and close. Photo: Mike Grimmett/MIT CSAIL

“Xstrings” method enables users to produce cable-driven objects, automatically assembling bionic robots, sculptures, and dynamic fashion designs.

3D printing approach strings together dynamic objects for you

In this episode, we explore how a generative AI tool is marking a major milestone in biology and accelerating advancements in healthcare, genetics, and drug development.<iframe height="200px" width="100%" frameborder="no" scrolling="no" src="https://player.simplecast.com/8b738738-5a69-4f97-ac33-8d48a50ec427?dark=false"></iframe> <hr /><h3>Episode Notes</h3>In this episode, we explore how a generative AI tool is marking a major milestone in biology and accelerating advancements in healthcare, genetics, and drug development.Become a founding reader of our newsletter: <a href="http://read.thenextbyte.com/">http://read.thenextbyte.com/</a><hr /><h2 id="isPasted">Transcript</h2>What's up folks, welcome back to the Next Byte podcast. And in this one, we're talking about DNA sequencing. Specifically, we're talking about a team over at Stanford that has created a ChatGPT-like AI model that can predict what comes next if you give it any DNA sequence, including yours.  that's got you a little bit spooked or excited or just curious. Well, then let's get into it.What's up friends, this is The Next Byte Podcast where one gentleman and one scholar explore the secret sauce behind cool tech and make it easy to understand.Farbod: This is another one of those biology ones. So, you already know I'm gonna struggle, but that's okay. We learn when we struggle. I was…Daniel: You just need to test your limits, man!Farbod: And that's what I'm doing. I'm trying here, but it was so interesting that I knew we needed to talk about it. So, for the audience, please bear with me. This is not my area of expertise, but God am I trying. So, for this episode, we're going to Stanford. You know the West Coast is the best coast, but these folks at Stanford, they're doing some crazy things with DNA sequencing.  And to be completely honest, they've kind of done this before, but now they're doing it better. So, what am I talking about? They've developed a chatGPT-like model, right? It's structured like a large language model, but instead of processing the meaning of the word that you're typing or the paragraph that you're writing or whatever and then giving you an answer or a follow-up or completing your train of thought, it takes as an input. A sequence of nucleotides, a sequence of DNA, and it completes it for you or it makes sense of it and it tells you what genes might be associated with each other. Now, before we get into that, I think we got to take it a couple steps back and by we, I mean me because I know I need to take it, a couple steps back. So, they did an amazing job in this article, by the way, explaining things like you're a five-year-old, which again is wonderful for me, and they have a three-minute video that I highly recommend you check out. It's going to be attached to the show notes. But they explained the issue at hand like this. They said, imagine you're reading the book, and this book has three billion letters in it, right? And every one of those letters is a nucleotide. These nucleotides make up the DNA that everything we know of in this world is pretty much composed of. And it's actually kind of straightforward. We represent them as four letters, A, C, G, and T. And standalone, they don't really mean much, but the sequence of them in different patterns together make up specific genes. Now, as we know, if you've been watching the news, this gene causes this, and poor, broken nucleotide sequences can, for most people, be harmless. For some people, it can cause cancer. So, there's a lot of value in understanding what those sequences mean, how they're related to each other, et cetera, et. Now, as I mentioned, this team had already worked on a chatGPT-like model before called the EVO-1 that was trained using 300 billion nucleotides, mostly from bacteria and stuff like that, to help them proof of concept this idea of, if we had a model that could predict what comes next. Could we better understand what the next evolutionary step would be for this plant or these bacteria or this human? Or could we better understand how the sequence that is at the one millionth element is related to the one at the 100,000th element? And if so, what does that tell us about the chances that you might have cancer? Or could we edit this out? The possibilities and the downsides of what already exists, basically.Daniel: Well, and when we talked about the technological development of having sequenced the human genome several decades ago, that didn't necessarily crack the code for us on what everything in human DNA means. That was just us looking at the DNA and writing a list, writing that three billion letter long book of just A’s, C’s, G’s, and T’s. It's awesome that like there's only four letters, but essentially, we didn't understand how those letters comprise genes and genes, they liken it in the article to like words. So, like basically, the major development in sequencing the human genome was like figuring out the alphabet and the order of the letters in the alphabet. But we did not yet understand the vocabulary. We didn't understand the words. And beyond that, we don't understand the grammar about how you put several words together to create phrases. And that's how physical characteristics are expressed or through a combination of several different genes. So, this is essentially helping us bridge the gap. And like in my mind, truly cracked the code on the meaning of DNA. If we can start to predict protein form and function by looking at the order of the A's, C's, G's and T's, predict harmful slash beneficial genes, potentially create new genetic sequences for medicines or treatments like this. This is bridging the gap between the letters in the physical realm, whereas before it was awesome that we understood what word of the letters were in.Farbod: You know, just like EVO2 is making sense of these nucleotide sequences, I'm happy you're here to make sense of my train of thought about biology.Daniel: EVO2 wouldn't exist without EVO1, buddy.Farbod: You're right. And like, I guess that frame of thinking is even better when comparing it to something like ChatGPT or really any other large language model, because the key breakthrough there, I think we mentioned it five episodes ago. The key breakthrough there was the transformer architecture, which said in relation to this wider body of text, what does this letter mean and this letter mean, instead of trying to make sense of a sequence of words back-to-back, which then lost meaning once you reach the 50th word. So again, they've taken the same underlying engine here, but now applying it to what does this sequence of genes mean, these nucleotides mean. And I think, I mentioned that EVO1 had 300 billion nucleotides, which already sounds quite impressive, but it was mostly bacteria and whatnot. Well, they upped it for EVO2, and now they include animals, plants. Overall, there's nine trillion nucleotides that are represented in this model. The only thing that they left out by design was viruses. The team said they didn't want this tool to be something that bad actors could use to develop and refine existing viruses, which I personally thank them. I think no one wants another round of the coronavirus. So, kudos for thinking ahead on that.Daniel: And this is like, it's pretty monumental here. So, in addition to like excluding viruses, right? Basically, except for viruses, the training data now is 27 times bigger than before. It includes all known living species that we have a DNA sequence for, plus some that are extinct. So, it's like, it's pretty much everything that we've ever sequenced ever, except for viruses so that we don't have people going, creating designer viruses to go try and get people sick. But every living being that we have the DNA sequence for has been included in the training data for this next generation. That's a big deal to increase your training data size, your training data set by a factor of 27, right? It's not like they've trained on 10 % more sequences than before. This is a huge deal.Farbod: Absolutely. And not only have they increased the number of data points that they're training on, but the input is also, what does ChatGPT call them, the number of tokens that you can input for a query? Yeah.Daniel: Yeah.Farbod: So, they've upped it to a one million letter sequence of nucleotides. So, you can have one million letters of combination of ACGT and it can then do whatever you want with it, analyze it, predict the next set of sequences, cetera, et. And I was wondering why one million? Apparently in the world of biology, the one million mark is, it's critical because it's long enough that it takes into account historically significantly far enough genes to make sense of rather than just taking into account the recent developments or deficiencies.Daniel: That makes sense. I appreciate the significance around there. And this makes me feel more so.  ChatGPT is an awesome analogy to give people, especially because I feel like a lot of people have had exposure to ChatGPT. But I'm hoping within our audience, maybe there's folks who've had a greater exposure to things like a co-pilot in coding or things like cursor composer. This actually feels a lot like cursor composer to me where in the cursor editor, you can go in the composer bar and you can have your code base living there, which is like a sequence of DNA. And you can tell it, hey, I want to generate a change to do this to the code  and composer will go and make those changes based off of its understanding of the code. This feels a lot like that, right? So, some of the technical features that it has, similar actually again to cursor composer is like autocomplete. They make a big deal about it in cursor. They call them tabs, but basically like you're writing and it understands what you're trying to code and you can just hit tab and it completes it, right? Autocomplete for code. They have autocomplete for DNA here based off of patterns in DNA sequences. They also have prediction models that can understand real world function. So instead of saying like change all the A's to C's or you know, control F my ACGTs and change them to TCGAs, you can say, I actually just want to change how this physical characteristic appears in the real world. And then it'll go change the DNA to reflect that. And then the interesting part, which is really awesome in my mind, it tends to be somewhat controversial. But we've seen a lot of work with CRISPR gene editing, which basically allows us to like sequence DNA, fabricate it, and then inject it into a DNA sequence. And then in a living being and basically edit a living being's DNA. They're able to essentially predict what the outcome of CRISPR gene editing will look like in the real world to propose edits essentially propose future experiments and tests.Farbod: Yes. That's what I gonna bring up I think, you know, the audience might have mixed feelings about that but what stood out to me? They were like look within this model with an EVO2 we can whenever you're predicting a new gene, we can tell you if it already exists if it doesn't if you implement it like what kind of behavior it could have, and then obviously you can do lab testing, put it into a living cell and see how it pans out. One thing that I thought was interesting in regards to CRISPR and gene editing, they were like, what if we could use this tool to modify bacteria to consume microplastics and to clean up oil spills, right? So again, I know it's a mixed feeling type of topic, especially as it relates to human beings, but the benefits of this tool are actually pretty significant. And even on the human-Daniel: This doesn't necessarily dictate how the findings are applied, right? This is an engine for understanding DNA, right? That's what we should be excited about, is it's an engine for us to understand what's going on. Even if you decide not to go edit your genes, to get rid of a disease, you can understand what diseases you might be predisposed to based off of your DNA.Farbod: Yeah, and you know, most of the stuff that they talked about are all the positives that we can all agree on, like modifying the bacteria. They said this can be used to significantly cut down on the discovery phase of new drug development because you can find which proteins work best for addressing whatever symptom. We talked about these two episodes ago, I think, on the snake venom episode, which has been a hit, by the way. They did mention that EVO2 could help with human evolution because we could predict what genes could be beneficial to us, but that's a topic for another day. I think what we should focus on here is that this is an incredible platform that they have open source. It's available to all researchers that they want others to use in their workflow and build on top of so that we can make better drugs and help our environment.Daniel: Well, and I think two really important things to mention. And you mentioned one of them and I kind of want to double down on it. One of them is direct quote from the researchers. They said it's really, really good at drug discovery, which is awesome. So obviously, helping identify treatments for potential diseases is awesome. But one of the other things that they can mention is like they, this model can distinguish between harmless DNA mutations to disease, disease causing ones. So, where we've got a lot of concern around free radicals and/or mutations in your DNA, potentially cancer causing, as you mentioned before, is like, we're trying to limit exposure to anything that could cause any type of mutation in your DNA. And that's where we get a lot of conflicting advice from people like, oh, like don't put on sunscreen, but also don't get sunburned and don't eat this and don't eat that. And don't do that. Like it feels like you're, you're screwed either way. I feel like this will potentially help us get more clarity around which types of causes for DNA mutations are most likely to cause disease and then help us hone our focus on like, what's the 80-20? What's the Pareto principle? Like what's the 20% of effort that I can do to protect myself from 80% of bad outcomes? I feel like that's one of the most important things that you and I will experience in our day-to-day life is a little bit more clarity around a lot of the conflicting guidance that we get. I think the most specific one that I think of is like around sun exposure. Like they're like, you need sun exposure for vitamin D, but don't get so much sun exposure that it causes mutations in your skin can cause melanoma. So, if you're outside, make sure you put on sunscreen, but also sunscreen can like cross through the blood brain barrier and cause disruptions in your hormones. Try and give us some clarity around a lot of the conflicting advice like that, where it feels like you can't win either way. Like, hopefully this will help us understand more what changes to make in a day-to-day life that actually have an impact on the presence of disease in our DNA.Farbod: Dude. Yeah, I totally agree that was a good hot take that I completely missed. And the sunscreen one, I'm totally with you. I think about it every morning when I put on my sunscreen. With that said, I'm going to wrap things up. So, folks, if you've heard about DNA sequencing and what a miracle it was that we cracked it a couple decades ago, you might be shocked to hear that it didn't crack the code all the way. Look, we understand what the nucleotides are that make up our DNA. You know, the four different ones, the A, C, G and T. But these folks over at Stanford are now developing a model or have already developed a model that can make sense of the different genes that are part of this DNA sequence and how they interact with each other. But more importantly, almost like you're using ChatGPT, it can predict what comes next. Now, why is this valuable? Well, by understanding the relation between the different genes, they can understand what is harmful, what can be used to develop new tools, how we can modify an existing sequence to give us beneficial properties. For example, one they called out was modifying bacteria to eat microplastics or clean up oil spills. And the next bit, it could even help us understand what good way we can go for evolving the human genome so that we get all the best properties possible.Daniel: That's Pretty fireman.Farbod: Sweet. That's the pod.Daniel: All right. See you.<hr />As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.To learn more about this show, please visit our<a href="https://www.wevolver.com/profile/the.next.byte"> shows page</a>. By following the page, you will get automatic updates by email when a new show is published. Be sure to give us a follow and review on<a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" target="_blank" rel="nofollow"> Apple</a> podcasts,<a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" target="_blank" rel="nofollow"> Spotify</a>, and most of your favorite podcast platforms!--The Next Byte: We're two engineers on a mission to simplify complex science &amp; technology, making it easy to understand. In each episode of our show, we dive into world-changing tech (such as AI, robotics, 3D printing, IoT, &amp; much more), all while keeping it entertaining &amp; engaging along the way.

In this episode, we explore how a generative AI tool is marking a major milestone in biology and accelerating advancements in healthcare, genetics, and drug development.

Podcast: Stanford Predicts The Next Human Evolution

<html><head></head><body>Unlock unlimited sports potential (Extra large joint movement space angle, 23~43 joints) Force control of dexterous hands, manipulation of all thingsImitation &amp; reinforcement learning driven Robot world model, let’s create it together Unitree G1 Price from $16K (Tax and Shipping cost excluded)More introduction:&nbsp;<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqbFpMZ0ZSV05IaDdTbEZuQnlFN1B3cDgzbnY0d3xBQ3Jtc0trTXhubEF2aWpndUhNLUFQajBBdmJObEFrRmZlcWdEdTN3dm1Fdzd0LUhGeVhxRF9HUUYwdl9NM2x5UnplTlYtR05zdkxSdUhvUk0zNktiWGhvdlpkNHhpazlUOVhpNHk5dmI3cEJRWWI2U3JQWEttTQ&amp;q=https%3A%2F%2Fwww.unitree.com%2Fg1&amp;v=GzX1qOIO1bE" rel="nofollow" target="_blank" data-immersive-translate-walked="fad7c807-08d6-4a00-ad03-0c3b7086529c">https://www.unitree.com/g1</a>Official Website: www.unitree.com&nbsp;Sales contact: sales_global@unitree.cc</body></html>

AI Avatar  Price from $16K

Unitree Introducing  Unitree G1 Humanoid Agent

720° Spin Kick - Hear the Impact! Kung Fu BOT Gameplay RAW. (No Speed-Up) (Do not imitate, please keep a safe distance from the machine)

720° Spin Kick - Hear the Impact! Kung Fu BOT Gameplay RAW. (No Speed-Up) 
(Do not imitate, please keep a safe distance from the machine)

Kungfu BOT GAME

We have continued to upgrade the Unitree G1's algorithm, enabling it to learn and perform virtually any movement. What other moves would you like to see. Do share with us in the comments. (Please keep a safe distance from the robot.)

We have continued to upgrade the Unitree G1's algorithm, enabling it to learn and perform virtually any movement.What other moves would you like to see. Do share with us in the comments. (Please keep a safe distance from the robot.)

Kungfu BOT: Unitree G1

Across the UK and Europe – and indeed globally – there is broad agreement that a focus on STEM - Science, Technology, Engineering, and Math – is essential. One year ago, &nbsp;the <a href="https://www.stemcoalition.eu/publications/conference-future-stem-europe">EU STEM Coalition</a> hosted a gathering with the objective of highlighting the importance of STEM education in Europe to ensure Europe's future competitiveness and ability to cope with transition. In the UK, previous governments have announced a range of measures, including <a href="https://www.computerweekly.com/news/252528203/Government-announces-490m-education-investment#:~:text=The%20government%20has%20announced%20almost,development%20in%20several%20different%20disciplines.">funding worth almost £490M&nbsp;</a> for universities and colleges to help deliver better STEM education. The fund will contribute to better facilities, equipment and course development in several different disciplines. Immediately, upon its election victory in the UK, the new Labour administration was urged by leading industry body, EngineeringUK, ‘to take immediate action to tackle the growing skills shortage in STEM fields’. Even before being elected, policies were being put in place, such as a commitment to publish a cross-government action plan to break down barriers in STEM, &nbsp;setting ‘a clear direction for government policy around diversity in STEM’ to improve ‘equality, diversity and inclusion (EDI) in STEM central to work across government’.<a href="http://www.mikroe.com">MikroElektronika</a> (MIKROE) is a proud advocate of STEM activities. MIKROE is an embedded solutions company with a mission to reduce development time and costs by introducing innovative hardware and software products based on proven standards. In 2011, the company invented the <a href="https://www.mikroe.com/mikrobus">mikroBUS</a>™ development socket standard and the compact add-on <a href="https://www.mikroe.com/click/">Click™</a> boards for peripherals that use the standard. Click boards enable designers to get to work immediately without having to develop their own hardware. This can cut months from the development cycle and save considerable expense. Currently, over 1700 boards are available that address wireless connectivity, sensors, power management, interfacing, displays, motor drives, HMI and more. Many of the world’s top microcontroller makers, including Microchip, NXP, Renesas, Silicon Labs and Infineon include the mikroBUS socket on development boards.Recently, MIKROE unveiled&nbsp;<a href="https://embeddedwiki.com/">EmbeddedWiki</a> – the world's largest embedded projects platform that already details over 1,000,000 projects, based around the huge and diverse Click board product range.&nbsp;<h2 dir="ltr">The idea behind EmbeddedWiki?</h2>The internet is a place where everything is scattered, and it can take a lot of time to find required information. Even when an answer is found, after hours and hours of searching, there is no guarantee that the solution provided will work or be accurate.EmbeddedWiki uses pre-designed and standardized hardware and software solutions, and serves as a starting point for developing customized products or applications. The platform covers 12 topics and 92 applications. Each entry contains a full description of the project, plus a list of parts that is required, schematics, 100% validated, working code and a step-by-step assembly guide. Therefore, an EmbeddedWiki project presents all the essential information for a successful result – all available from one source.In this issue we are going to focus on four projects concerning health. But visitors to the site will quickly see that there are very many examples of similar projects using different MCUs, so they can delve deep, and drill down to find a project based on devices of their choice.<h2 dir="ltr">Cardiovascular clarity: ECG excellence for a healthier you</h2>For this <a href="https://embeddedwiki.com/articles/template38-with-ecg-4-click/ecg-4-click-arduino-uno-rev3-necto-atmega328p">project</a> you will need: the <a href="https://www.mikroe.com/ecg-4-click">ECG 4 Click</a> board, an <a href="https://store.arduino.cc/en-dk/products/arduino-uno-rev3">Arduino UNO Rev3</a> development board; and the <a href="https://www.mikroe.com/necto">NECTO Studio</a> compiler. MCU: ATmega328PECG 4 Click is based on the BMD101, a highly integrated specialized bio-signal sensing SoC from NeuroSky, which produces heart-monitoring-related ICs and applications. This IC features complete HR and ECG functionality: the analogue front-end (AFE) section contains a very precise and low-noise instrumentation amplifier (LNA), which allows very low bio-signals generated by the heart to be amplified, enabling the 16-bit ADC to be able to sample them. These voltage impulses are naturally weak - in the range of a few millivolts, even microvolts. Therefore, any external interferences can obscure them. Interference might be produced in the heart itself or as the result of other muscular activity. Therefore, the input signal from the electrodes is processed by several filtering sections, both in the analogue (HP filter at the input) and digital domains (LP filter at 100 Hz and BP filter for removing the 50/60 Hz hum from the mains).&nbsp;<h2 dir="ltr"><a href="https://embeddedwiki.com/articles/template43-with-eeg-click/eeg-click-nucleo-64-with-stm32l476rg-mcu-necto-stm32l476rg">Your brain's story, captured in every wave</a></h2>You will need:&nbsp;<a href="https://www.mikroe.com/eeg-click">EEG Click</a> board;&nbsp;<a href="https://www.st.com/en/evaluation-tools/nucleo-l476rg.html">Nucleo-64 with STM32L476RG MCU</a>; and the&nbsp;<a href="https://www.mikroe.com/necto">NECTO Studio</a> compiler. MCU: STM32L476RG.<a href="https://embeddedwiki.com/articles/template43-with-eeg-click/eeg-click-nucleo-64-with-stm32l476rg-mcu-necto-stm32l476rg">EEG Click</a> allows monitoring of brain activity. Although not suitable for clinical examination, it is quite sufficient to allow some insight into brain activity. EEG click is equipped with a high-sensitivity circuit which amplifies faint electrical signals from the brain, allowing them to be sampled by a host MCU. To allow sufficiently high gain with no interference, EEG click uses the Texas Instruments’ INA114, a precision instrumentation amplifier, LASER trimmed for very low offset voltage, featuring very good common mode rejection ratio. Since ‘brain waves’ can be both positive and negative, EEG click uses a virtual GND at the potential of 2.048V. This also helps to reduce the noise from the common GND, improving the quality of the readings. The amplified brain activity signal is available at the AN pin of the mikroBUS™, allowing sampling by the host MCU.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1740047666932-eeg-click-banner.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2 dir="ltr">Have you got the fever?</h2>You will need:&nbsp;<a href="https://www.mikroe.com/fever-click">Fever click</a> board;&nbsp;<a href="https://www.microchip.com/en-us/development-tool/dm164150">Curiosity Nano with PIC18F57Q43</a> eval kit; and the&nbsp;<a href="https://www.mikroe.com/necto">NECTO Studio</a> compiler. MCU:&nbsp;PIC18F57Q43<a href="https://embeddedwiki.com/articles/template36-with-fever-click/fever-click-curiosity-nano-with-pic18f57q43-necto-pic18f57q43">Fever Click</a> is used for monitoring the body temperature, or it can be set to alert about ‘fever/no fever’ states (A fever is considered to be when the human body temperature exceeds 37.5℃). This Click board is based on the MAX30205, a human body temperature sensor from Analog Devices. The sensor converts temperature measurement to a digital form using a high-resolution sigma-delta ADC. The sensor can work in one-shot mode and shutdown mode, which helps reduce power usage. In addition, it features the selectable timeout, which prevents bus lockup and separate open-drain overtemperature shutdown (OS) output that operates as interrupt or as comparator/thermostat output.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1740047634173-fever-click-square.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2 dir="ltr">Real-time heart rate and blood oxygen saturation data</h2>You will need:&nbsp;<a href="https://www.mikroe.com/oximeter-2-click">Oximeter 2 Click</a> board;&nbsp;<a href="https://www.mikroe.com/clicker-2-kinetis">Clicker 2 for Kinetis</a> dev board; and the&nbsp;<a href="https://www.mikroe.com/necto">NECTO Studio</a> compiler. MCU:&nbsp;MK64FN1M0VDC12.<a href="https://bwwcomms.sharepoint.com/sites/BWWFileServer/Shared%20Documents/Clients/MikroE/Track%20your%20blood%20oxygen%20levels%20with%20ADPD144RI%20and%20MK64FN1M0VDC12%20%7C%20EmbeddedWiki">Oximeter 2 Click</a> is a compact add-on board suitable for measuring blood oxygen saturation. This board features the ADPD144RI, a PPG optical sensor for photoplethysmography detection of blood oxygenation from Analog Devices. It combines LED emitters and sensitive 4-channel photodiodes with a custom ASIC that provides optical isolation between the integrated LED emitters and the detection photodiodes to improve the signal-to-noise ratio (SNR). PPG detection of blood oxygenation is achieved by synchronous detection in red and infrared wavelengths. Synchronous measurement allows rejection of both DC and AC ambient light interference with low power consumption.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1740047648328-oximeter-2-click-banner.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2 dir="ltr">Everything in one place</h2>With these, and all other EmbeddedWiki projects, the user will find everything they need at a single url. Starting with a description of the project, entries include a description of the required hardware (Click board, development board and MCU), step-by-step assembly instructions and schematic. Pins are mapped, working code and library descriptions are provided, and links to all other resources given. NECTO is free for non-commercial uses, and the Click boards mentioned here range in price from just $13 to $55. Click <a href="https://embeddedwiki.com/">here</a> to get started.

EmbeddedWiki is the world's largest embedded projects platform that already details over 1,000,000 projects. 

STEM, health and EmbeddedWiki

<h2 id="isPasted">What Dance Would You Like to Perform with Unitree G1?</h2>With the upgraded algorithm, G1 can learn any dance. Leave a comment to tell us what dance you'd like to see！

With the upgraded algorithm, G1 can learn any dance. Leave a comment to tell us what dance you'd like to see！

What Dance Would You Like to Perform with Unitree G1?

<section id="isPasted">When you think about cancer research, thoughts go quickly to biological tests, drug testing, and patient studies. But what if we could use engineering to discover how cancer cells manage to leave the tumor to wander through our bodies? If we know how they do that, we could stop them right then and there. The relatively new organ-on-a-chip technology allows researchers like Mohammad Jouybar to build a biomechanical model of specific cases out of the human body to closely study how cancer behaves.</section><section tabindex="-1">TU/e researcher <a href="https://www.tue.nl/en/research/researchers/mohammad-jouy-bar" target="_blank">Mohammad Jouybar</a> is an engineer who has been very motivated to make a difference in health care from the start of his career.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1738889381375-csm_BvOF_2025_0127_0435+Mohammad+Jouy+Bar_bf626185da.jpg" style="width: 100%px;" class="fr-fic fr-dib">Mohammad Jouybar at work in the Microfab laboratory. Photo: Bart van OverbeekeJouybar says: “When I was looking for a PhD, the offer from Jaap den Toonder to build an organ-on-a-chip research model was exactly what I was looking for. Even though I never expected to find myself working in Mechanical Engineering as a bioengineer, it couldn’t have been a more perfect fit.”<h3>Organ-on-a-chip technology</h3>“The organ-on-a-chip technology is still relatively new in the field of disease modeling and therapeutic testing. I think it’s been around for about fifteen years,” says Jouybar. “It is mainly gaining importance as an alternative or supplementary option for animal models. It’s a more ethical and less expensive choice to gain the same insights.”<blockquote>Organ-on-a-chip offers a smarter, ethical, and cost-effective alternative to animal testing.Mohammad Jouybar</blockquote></section><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1738889430453-csm_BvOF_2025_0127_0239+Mohammad+Jouy+Bar_141c8ebbe8.jpg" style="width: 100%px;" class="fr-fic fr-dib">Close-up of the chip used in the breast cancer study. Material containing the cancer cells was placed in the left boxes. In the long cannula in the middle, the blood vessels were grown. The fluid streams were connected to them. It was then possible to measure how many cancer cells migrated through the vessels in the tissue in the right boxes. Photo: Bart van Overbeeke“That’s what intrigued me when I learned to work with the technology during my MSc studies in Milan, and why I went actively looking for a PhD to work with this technology.”In an organ-on-a-chip, researchers typically grow human organ cells in a hydrogel and/or in tiny microchannels. Because they grow the cells, they can determine exactly what type of cells they grow next to each other and what specific biomechanical cues to apply, such as blood flow within channels or mechanical stretch affecting cell-cell interaction.Effectively zooming in on a single function of an organ or single mechanism they want to study.<iframe width="640" height="360" src="https://www.youtube.com/embed/LK7L6vgGNcI?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>“There are many startups who have jumped at the opportunity to make organ-on-a-chip, or even cancer-on-a-chip models for regular testing in clinical settings. However the industry does not have a standard organ-on-a-chip model among the available models yet. Which makes it difficult to assess and compare results.”“Also, in academia, we want to study new settings, which will always call for making innovative models. And that’s what I did during my PhD.”<h3>First model</h3>There are several models Jouybar designed, built, and grew for his PhD. Jouybar: “My PhD was not very defined or detailed at first. The team wanted to study the metastatic phase of cancers. And that’s not a single event that happens, but rather a cascade of consecutive processes.”<blockquote>The metastatic phase of cancer isn't a single event - it's a cascading process.Mohammad Jouybar</blockquote><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1738889473088-csm_BvOF_2025_0127_0337+Mohammad+Jouy+Bar_9d2fcf783a.jpg" style="width: 100%px;" class="fr-fic fr-dib">Mohammad Jouybar places a sample in the incubator for measurements in the Mircrofab lab. Photo: Bart van OverbeekeIn metastasis,&nbsp;cancer cells break away from where they first formed (primary cancer), travel through the blood or lymph system, and form new tumors (metastatic tumors) in other parts of the body. The metastatic tumor is the same type of cancer as the primary tumor.“<a href="https://www.tue.nl/en/research/researchers/jaap-den-toonder" target="_blank">Jaap den Toonder</a> asked me to design and build a model to study how breast cancer cells leave their tumor, invade the tissue, and enter the bloodstream. We wanted to study how these cells invade the bloodstream from the breast duct.”The team chose to study breast cancer - <a href="https://www.mayoclinic.org/diseases-conditions/dcis/symptoms-causes/syc-20371889" target="_blank" rel="noreferrer">ductal carcinoma in situ</a> -because it is very prevalent and is a good case for studying the metastatic process.“We know that the cancer cells invade the blood or lymphatic vessels, but how some of these steps occur, especially the initial invasion steps, are not well known. And once the cells enter the blood vessel, they can travel anywhere,” says Jouybar.“We could not mimic the entire process on our chip, of course. So, we focused on the initial step of metastasis because little was known about it.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1738889496783-csm_Untitled_0c4666d5c5.jpg" style="width: 100%px;" class="fr-fic fr-dib">The tiny size of the chips allows for higher throughput models including several chips. The multi-Lumina-Chip includes 9 single chips on a platform, compatible with multi-channel pipetting. Photo: Mohammad Jouybar<h3 id="isPasted">Building the cancer-on-a-chip</h3>The first step is to build, or rather grow, the elements of your cancer-on-a-chip. In this case, the cancer cells are in a microchannel within the chip, emulating the breast duct, the surrounding hydrogel mimicking the structural (stromal, ed.) tissue, and the neighboring microchannels mimicking the tiny blood vessels.Jouybar fabricated the circular cross-section channels on a chip, a similar geometry found in human blood vessels. Next, he could vary the flow through these channels to study the effect of various types of flows on blood- or lymphatic vessel cells.“In <a href="https://pubmed.ncbi.nlm.nih.gov/37914546/" target="_blank" rel="noreferrer">one of our studies</a>, I have shown that the flow rate has an effect on the orientation of cells lining the blood or lymphatic vessels we grow on the chip. The chip is 2-3 centimeters squared, but the vessels are only around 10-100’s micrometers in diameter. Just like the tiny vessels in the tissue we want to study.”Growing the model to mimic living tissue is a challenge all of its own. “We had different components in the model: the breast ducts, the surrounding tissue, and the blood vessels. The trick to building the model with all those components adjacent to each other was to compartmentalize building those elements,” says Jouybar.“We used the facilities in our labs, like a femtosecond laser and 3D sugar printing, to build the circular geometries of the blood vessels. Additionally, we had to make sure that fabricated reservoirs were fully working to connect the models to the pumps for the blood flow or just simply for exchanging culture media.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1738889537492-csm_BvOF_2025_0127_0220+Mohammad+Jouy+Bar_309f8f747a.jpg" style="width: 100%px;" class="fr-fic fr-dib">Mohammad Jouybar with the chip for the femtolaser used to make the molds for the chips. The molds are made of glass, the chips themselves of plastic. Photo: Bart van Overbeeke<section tabindex="-1" id="isPasted"><h3>Including lymphatic vessels</h3>In a collaboration with Amsterdam UMC, Jouybar included not only blood vessels but also built lymphatic vessels in the cancer-on-a-chip models.Jouybar: “This was a simpler model from a fabrication point of view because we fabricated a microchannel cast in hydrogel utilizing a thin acupuncture needle. We added lymphatic cancer cells (B cell lymphoma) and fibroblasts to a hydrogel matrix.”“And then, we grew the lymphatic microvessel, lined by lymphatic endothelial cells, inside the hydrogel. With this model, we studied how donor’s specific fibroblasts and lymphatic vessel cells influence the movements of cancer cells in and around lymphatic vessels.”Both models focus on the step where the cancer cells start to move from their original location, where they might still be very treatable, throughout the body. The models help to understand what is happening on a fundamental level and can also help to study which types of medicine might affect the key mechanisms of the cancer. This opens up whole new areas of drug development and treatments.<h3>The value of cancer-on-a-chip</h3>“Depending on the type of cancer you are studying, due to the broad area of oncology, you can build a model to answer questions for the specific type of cancer and tissue, or even specific patient you are studying, so-called personalized medicine,” says Jouybar. “The models help us to fill in the blanks of how cancer originates, develops, and moves.”</section><section tabindex="-1"><blockquote>The cancer-on-a-chip models help us to fill in the blanks of how cancer originates, develops, and moves.Mohammad Jouybar</blockquote>“I really enjoy this type of collaborative research, where medical research, mechanical engineering, and biomedical engineering are colliding. We cannot do one without the other, and I expect much from how engineering can assist and boost medical research,” concludes Jouybar.</section>

Mohammad Jouybar shows the chip he used to do his research on breast cancer. Photo: Bart van Overbeeke

During his PhD research, biomedical engineer Mohammad Jouybar explored how to build specific organ-on-a-chip or even cancer-on-a-chip devices.

Cancer-on-a-chip technology advances our understanding of how cancer operates

In this episode, we explore how tiny wireless antennas use light to monitor cellular communication with groundbreaking precision.

Podcast: Tiny Antennas for Big Cellular Insights

Experiments from the Caltech lab of Chiara Daraio, G. Bradford Jones Professor of Mechanical Engineering and Applied Physics and Heritage Medical Research Institute Investigator, have yielded a fascinating new type of matter, neither granular nor crystalline, that responds to some stresses as a fluid would and to others like a solid. The new material, known as PAM (for polycatenated architected materials) could have uses in areas ranging from helmets and other protective gear to biomedical devices and robotics.<iframe width="640" height="360" src="https://www.youtube.com/embed/Z-P7lfW-p-8?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>PAMs in Action.&nbsp;Credit: Wenjie Zhou and Peter Holderness/CaltechPAMs are not found in nature, though their basic form is known to us through the millennia-old manufacture of chain mail: small metal rings linked together to form a mesh, most often used as a flexible form of armor. PAMs, however, are like chain mail on steroids. Following the basic principle of interlocking shapes, like those found in a chain, PAMs are made up of a variety of shapes linked together to form three-dimensional patterns whose configurations are almost unimaginably variable. The resulting materials, which Daraio and her colleagues have rendered using 3D printers, exhibit behaviors not found in other types of materials.Wenjie Zhou, postdoctoral scholar research associate in mechanical and civil engineering, has been working on these types of materials for two years in Daraio's lab. "I was a chemist, and I wanted to make these structures at a molecular scale, but that proved too challenging. In order to get answers to the questions I had about how these structures behave, I decided to join Chiara's group and study PAMs at a larger scale."The PAMs that Daraio's group created and studied were first modeled on a computer and were designed to replicate lattice structures found in crystalline substances but with the crystal's fixed particles replaced by entangled rings or cages with multiple sides.These lattices were then printed out three-dimensionally using a variety of materials, including acrylic polymers, nylon, and metals. Once the PAMs could be held in the palm of one's hand—most of the prototypes are 5-centimeter (2-inch) cubes or spheres with a 5-centimeter diameter—they were exposed to various types of physical stress. "We started with compression," Zhou explains, "compressing the objects a bit harder each time. Then we tried a simple shear, a lateral force, like what you would apply if you were trying to tear the material apart. Finally, we did rheology tests, seeing how the materials responded to twisting, first slowly and then more quickly and strongly."In some scenarios, these PAMs behaved like liquids. "Imagine applying a shear stress to water," Zhou says. "There would be zero resistance. Because PAMs have all these coordinated degrees of freedom, with the rings and cages they are composed of sliding against one another as the links of a chain would, many have very little shear resistance." But when these structures are compressed, they may become fully rigid, behaving like solids.This dynamism makes PAMs unique. "PAMs are really a new type of matter," Daraio says. "We all have a clear distinction in mind when we think of solid materials and granular matter. Solid materials are often described as crystalline lattices. This is what you see in the classic ball-and-stick models of atomic, chemical, or larger crystalline structures. It is these materials that have formed our conventional understanding of solid matter. The other class of materials is granular, as we see in substances like rice, flour, or ground coffee. These materials are made up of discrete particles, free to move and slide relative to one another."PAMs defy this binary classification. "With PAMs, the individual particles are linked as they are in crystalline structures, and yet, because these particles are free to move relative to one another, they flow, they slide on top of each other, and they change their relative positions, more like grains of sand," Daraio explains. "PAMs can be very different from one another. You can print them in squishy materials or hard ones. You can change the shape of each particle, and you can change the lattice that you use to connect these particles. Each of these parameters affects the behavior of the resulting material. But all of them show a characteristic transition between fluid and solid-like behavior. This transition may happen under different circumstances, but it always happens.""Architected materials have been a significant subfield in material science and engineering for the past 20 to 30 years," Daraio says. "But as hybrids between granular materials and elastic deformable materials, PAMs are exciting and new. We have theories to describe granular matter and theories to describe elastic deformable matter, but nothing that captures these in-between materials. It's a fascinating frontier that promises to redefine what materials are and how they behave."At this point, potential uses for PAMs are largely speculative but nevertheless intriguing, Daraio says: "These materials have unique energy-absorption properties. Because each element can slide and rotate and reorganize relative to each other, they can dissipate energy very efficiently," making them better candidates for use in helmets or other forms of protective gear than the currently used foams. This property makes them similarly attractive for use in packaging or in any environment where cushioning or stabilization is required.Experiments with microscale PAMs have shown that they will expand or contract in response to applied electrical charges as well as physical forces, suggesting possible uses in biomedical devices or soft robotics.Co-author Liuchi Li (PhD '20), now assistant professor of civil and environmental engineering at Princeton University, is enthusiastic about the future of PAMs: "We can envision incorporating advanced artificial intelligence techniques to accelerate the exploration of this vast design space. We are only scratching the surface of what is possible."This research is published in&nbsp;Science under the title&nbsp;<a href="https://www.science.org/doi/10.1126/science.adr9713">"3D polycatenated architected materials."</a> Co-authors include Zhou, Daraio, Sujeeka Nadarajah, Hujie Yan (MS '24), Aashutosh K. Prachet, and Payal Patel of Caltech; Li of Princeton University; and Anna Guell Izard and Xiaoxing Xia (PhD '19) of Lawrence Livermore National Laboratory (LLNL). Computational resources were provided by the High-Performance Computing Center at Caltech, and the research was funded by the Army Research Office, the Gary Clinard Innovation Fund, LLNL, and the US Department of Energy.

The new material, known as PAM (for polycatenated architected materials) could have uses in areas ranging from helmets and other protective gear to biomedical devices and robotics.

Reimagining Chain Mail: 3D Architected Materials That Adapt and Protect

Hello everyone, let me introduce myself again. I am Unitree H1 "Fuxi".&nbsp;I am now a comedian at the Spring Festival Gala, hoping to bring joy to everyone.&nbsp;Let’s push boundaries every day and shape the future together.A little surprise: the handkerchief can not only spin but can also be thrown out and automatically returned to its position.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzM4MDc3NzEzOTI3LeW+ruS/oeWbvueJh18yMDI1MDEyODIzMDMzNy5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib">

Debut at the Spring Festival Gala

Unitree H1: Humanoid Robot Makes Its Debut at the Spring Festival Gala

Unitree H1&nbsp;Deep Reinforcement Learning&nbsp;In-place Flipping Parameters:&nbsp;Weight: about 50kg&nbsp;Height: about 1.8m&nbsp;Actuator: electric motor

Deep Reinforcement Learning

Unitree H1

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biomedical devices

Scanning Electron Microscope (SEM) Machine in Laboratory

This article delves into the fundamental principles of SEM, various imaging modes and techniques, sample preparation methods, and the applications of SEM in different fields.

Biomedical Devices

Technical Guides

Scanning Electron Microscopy: A Comprehensive Guide

Profiles