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“Smart skin” can identify weaknesses in bridges and airplanes using laser scanner

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Recent research results have demonstrated that two-dimensional, on-demand mapping of the accumulated strain on metal structures will soon be a reality thanks to an engineered “smart skin” that’s only a fraction of the width of a human hair. By utilizing the unique properties of single-walled carbon nanotubes, a two-layer film airbrushed onto surfaces of bridges, pipelines, and airplanes, among others, can be scanned to reveal weaknesses in near real-time. As a bonus, the technology is barely visible even on a transparent surface, making it that much more flexible as an application.

Stress-inducing events, along with regular wear and tear, can deform structures and machines, affecting their safety and operability. Mechanical strain on structural surfaces provides information on the condition of the materials such as damage location and severity. Existing conventional sensors are only able to measure strain in one point along one axis, but with the smart skin technology, strain detection in any direction or location will be possible.

How “Smart Skin” Technology is Used

In 2002, researchers discovered that single-wall carbon nanotubes fluoresce, i.e., glow brightly when stimulated by a light source. Later, the fluorescence was further found to change color when stretched. This optical property was then considered in the context of metal structures that are subject to strain, specifically to apply the property as a diagnostic tool. To obtain the fluorescent data, researchers applied the smart skin to a testing surface, irradiated the area with a small laser scanner, and captured the resulting nanotube color emissions with an infrared spectrometer. Finally, two-dimensional maps of the accumulated strain were generated with the results.

Smart skin technology could be used to monitor the structural integrity in commercial jet engines. | Credit: CC0 via Pixabay, User: blickpixel

The primary researchers, Professors Satish Nagarajaiah and Bruce Weisman of Rice University in Texas, have published two scientific papers explaining the methods used for achieving this technology and the results of its proof-of-principle application. As described in the papers, aluminum bars with holes or notches in areas of potential stress were tested with the laser technique to demonstrate the full potential of their invention. The points measured were located 1 millimeter apart, but the researchers stated that the points could be located 20 times closer for even more accurate readings. Standard strain sensors have points located several millimeters apart.

What Are Carbon Nanotubes?

Carbon nanotubes (CNTs) are carbon molecules that have been structurally modified into cylinders, or rather, rolled up sheets of carbon atoms. There has been some evidence suggesting that CNTs can be formed via natural processes such as volcanic events. However, to really capitalize on their unique characteristics, production in a laboratory environment is much more efficient.

Several methods can be used for production, but the most widely used method for synthesizing CNTs is chemical vapor deposition (CVD). This process combines a catalyzing metal with a carbon-containing gas which are heated to approximately 1400 degrees Fahrenheit, triggering the carbon molecules to assemble and grow into nanotubes. The resulting formation resembles a forest or lawn grass, each trunk or blade averaging .43 nanometers in diameter. The length is dependent on variables such as the amount of time spent in the high heat environment.

An artistic depiction of a carbon nanotube. | Credit: AJC1 via Flickr, CC BY-SA 2.0

Besides surface analysis, carbon nanotubes have proven invaluable in many research and commercial arenas, their luminescence being only one of many properties that can improve and enable other technologies. Their mechanical tensile strength is 400 times that of steel while only having one sixth the density, making them very lightweight. CNTs also have highly conductive electrical and thermal properties, are extremely resistant to corrosion, and can be filled with other nanomaterials. All of these advantages open up their applications to include solar cells, sensors, drug delivery, electronic devices and shielding, lithium-ion batteries, body armor, and perhaps even a space elevator, assuming significant advances overcome its hurdles.

Next Steps

The nanotube-laced smart skin is ready for scaling up into real-world applications, but its chosen industry may take time to adopt given the general resistance to change in a field with long-standing existing technology. While awaiting embrace in the arena it was primarily designed for, the smart skin has other potential uses in engineering research applications. Bruce Weisman, also the discoverer of CNT fluorescence, anticipates its advantages being used for testing the design of small-scaled structures and engines prior to deployment. Niche applications like these may be the primary entry point into the market for some time to come. In the meantime, the researchers plan to continue developing their strain reader to capture simultaneous readings from large surfaces.

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Elon Musk

Elon Musk shuts down talk of TSMC taking over Terafab

Musk says Tesla and SpaceX will build and run Terafab, with TSMC limited to renting.

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SpaceX Terafab rendering

Elon Musk has drawn a firm line around who will be in charge of Terafab, the giant chip factory Tesla and SpaceX are planning in Texas.

Musk replied to a post on X arguing that Taiwan Semiconductor Manufacturing Company (TSMC) would most likely end up owning and operating the plant. “No, we will build and run the fab. Let there be ZERO doubt about that,” Musk wrote. “Maybe TSMC subleases part of the Terafab if they want, but nothing more than that.”

In plain terms, a sublease means TSMC could rent a section of the complex to make chips, similar to a tenant renting one floor of an office tower. The building, the equipment decisions and the daily operation would stay with Tesla and SpaceX.

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The comment shuts down speculation that started last week. On October 2, tech journalist Tim Culpan reported that TSMC was exploring ways to help run Terafab’s factories. Musk responded the next day that it was “just discussions, but something may come of it,” as Teslarati reported at the time. That left room for a scenario where the world’s largest contract chipmaker took the wheel. Musk’s latest post closes that door.

Elon Musk teases TSMC as potential Terafab partner

Some background helps explain why this matters. Tesla designs its own AI chips today but pays outside companies like TSMC and Samsung to manufacture them. Musk unveiled Terafab in March as a joint project between Tesla, SpaceX and xAI, arguing that existing suppliers cannot expand fast enough to meet his companies’ future demand. The goal is to produce enough chips each year to supply one terawatt of computing power, roughly 50 times what the entire global AI chip industry produces now.

Those chips are meant for Tesla’s Optimus humanoid robots, the Cybercab and Full Self-Driving computers, along with chips for SpaceX’s planned data centers in orbit. Owning the factory means Musk’s companies would not have to compete with every other chip customer for time on someone else’s production lines.

Intel is still part of the picture. The company signed on in April to help design, build and package chips for the project, and CEO Lip-Bu Tan told Bloomberg this week that Intel will keep working on Terafab despite the TSMC chatter.

The project moved from concept to construction planning over the summer. In August, SpaceX confirmed the Grimes County site about an hour from Houston, sent the county a $10 million payment under its tax abatement deal and said civil work would begin shortly. The first phase carries a $16.8 billion price tag, and total spending across all phases could reach as much as $119 billion.

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TSMC chairman C.C. Wei has said a new fab typically takes two to three years to build and another one to two years to reach full output. Tesla and SpaceX have never run one, which is why TSMC’s expertise drew so much attention. Musk’s answer suggests he would rather learn that process in house than hand control of a project this central to Tesla’s robotics and autonomy plans to an outside company.

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Elon Musk

Trump to hand Elon Musk a top honor that traces back to JFK

Trump will award Elon Musk the National Medal of Science at Thursday’s White House summit.

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elon musk and donald trump in front of a tesla cybertruck at the white house

Elon Musk is set to receive the highest honor the U.S. government gives to scientists and engineers.

President Donald Trump will present Musk with the National Medal of Science on Thursday at the White House’s Science: A New Golden Age Summit, Fox News Digital first reported on Wednesday. Google cofounder Sergey Brin, Nvidia CEO Jensen Huang and AMD CEO Lisa Su will receive the same medal, while Dell Technologies CEO Michael Dell and Microsoft CEO Satya Nadella will receive the National Medal of Technology and Innovation. A White House official later confirmed the list to Reuters.

“The Trump administration is grateful for the contributions of these incredible leaders in science and technology. These recipients are helping ensure America keeps leading the world in innovation,” White House spokesperson Liz Huston told Fox News.

It will be the first time Trump has presented either medal in his two terms. Congress created the National Medal of Science in 1959, and the National Science Foundation, which administers it, says 529 scientists and engineers have received it since. A presidential committee reviews nominees, but the president makes the final call.

Thursday’s group of medalists run or founded companies, and three of them sit at the center of the Super Intelligence hardware race that Musk competes in. Huang’s Nvidia supplies the GB300 chips filling SpaceX’s Colossus 2 cluster, while Su’s AMD is Nvidia’s biggest rival in data center GPUs.

Worth noting that Trump’s uncle, MIT physicist John G. Trump, received the National Medal of Science from President Ronald Reagan for his work on ionizing radiation and its uses in medicine and industry.

The Pentagon taps Elon Musk to design the battlefield of the future

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For Musk, the medal is the latest sign of how far his relationship with Trump has come since their 2025 split over the “Big Beautiful Bill” and his exit from DOGE. Last week, he sat at Trump’s left during a White House lunch where AI executives signed a voluntary safety accord, and Defense Secretary Pete Hegseth named him to help lead the Pentagon’s Project Meridian study on the future of warfare. Musk has also adopted the administration’s new vocabulary, saying on Sunday that SpaceXAI will be renamed SpaceXSI after Trump ordered federal agencies to replace “artificial intelligence” with “super intelligence.”

Musk has collected science honors before, including the Stephen Hawking Medal for Science Communication in 2019.

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Lifestyle

Tesla FSD changed its mind mid-intersection, and it may have saved a life

Tesla shares dashcam footage of FSD Supervised stopping mid intersection to avoid a T-bone crash.

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Credit: @BLKMDL3/X

Tesla is putting another Full Self-Driving save in front of its 24.8 million followers on X.

On Tuesday morning, Tesla’s main account shared a dashcam clip with the caption “FSD Supervised preventing T-bone crash.” The footage came from an owner posting as TheNewGrid, who described what happened at a stop sign: “I looked at the car coming to the stop sign figured they would stop, my car went, then came to a stop mid intersection as they flew by. Had I been manually driving this would have resulted in a crash.”

The sequence is the notable part. FSD had already started crossing when the other driver ran the stop sign. Instead of pressing on, the car braked hard in the middle of the intersection and let the crossing vehicle pass in front of it. By the owner’s own account, they had made the same assumption the software initially made, that the other car would stop, and would not have corrected in time.

The clip is the latest in a run of safety posts Tesla has amplified over the past several days. On Saturday, the company shared a video from Selling Sunset star Jason Oppenheim, who sold his Bentley for a Model Y and said he was buying Teslas with FSD for 10 of his employees. Ashok Elluswamy, who leads Tesla AI, followed up by writing that Tesla self-driving “reacts to other people cutting into your path with super-human response times.” On Monday, a Cybertruck owner posted footage of FSD moving across three lanes from a red light to clear a path for an ambulance approaching from behind.

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This recent clip also lands a few weeks after Tesla began shipping Automatic Collision Evasion with FSD v14.3.9, a feature that can activate FSD on the driver’s behalf when a frontal collision is imminent or the driver appears distracted. Elluswamy said in September that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” are coming with v15, the release Tesla has tied to round the clock Robotaxi operation.

The safety messaging matters beyond social media. Tesla has said FSD Supervised was 4.1 times less likely to crash than manual driving across 100 million kilometers on European roads, and it has been putting those figures in front of regulators. Eight EU countries have now approved FSD Supervised, with Croatia the most recent, but the EU’s bloc-wide vote originally set for October 6 has been pushed to December at the earliest.

FSD Supervised is still a Level 2 system, and the driver remains responsible at all times. Even heavy users find reasons to step in. Teslarati’s Joey Klender, who uses FSD for about 76 percent of his driving, laid out five recurring issues on Tuesday that still prompt him to intervene. Clips like this one show the other column of that ledger: moments where the software caught a mistake a human was about to make.

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