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Researchers find graphene can strengthen the brain’s neural signals

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A recent study from a group of researchers at the International School for Advanced Studies (SISSA) in Italy and the Catalan Institute of Nanoscience and Nanotechnology (ICN2) in Spain have demonstrated how graphene could be combined with neurological tissue, allowing the material to become a valuable tool for medicine and other biological processes.

In a statement to the IEEE Spectrum, Laura Ballerini, a researcher in neurons and nanomaterials at SISSA, stated that the results of the recent study demonstrate that graphene might tune neuronal activities by altering ion mobility at the cell interface depending on the how the single-layer graphene is engineered. According to the researcher, graphene-based nanomaterials have come to represent potential tools in neurology and neurosurgery.

“These materials are increasingly engineered as components of a variety of applications such as biosensors, interfaces, or drug-delivery platforms. In particular, in neural electrode or interfaces, a precise requirement is the stable device/neuronal electrical coupling, which requires governing the interactions between the electrode surface and the cell membrane,” she said.

Graphene has been dubbed as a supermaterial, thanks to its unique set of properties. Graphene, described in simplest terms, is a thin layer of graphite, the same material used in pencil lead. What is particularly remarkable with graphene is that it takes some near-miraculous properties when it is isolated from graphite. At one atom thick, graphene stands as the world’s first two-dimensional material ever discovered. It also boasts a tensile strength of 130 gigapascals, making it ~100 times stronger than steel. Apart from being thin and durable, graphene is also flexible, transparent, seemingly impermeable to most gases and liquids, and most of all, highly conductive.

These properties have allowed graphene to be viewed as a potential game-changer in several fields, including electronics, solar cells, semiconductors, and of course, biomedical technology. Just last year, researchers from the Graphene Flagship developed graphene-based field-effect transistors which have the capability to record brain activity in high resolution while maintaining an optimal level of signal-to-noise ratio (SNR).

Graphene is characterized by its hexagonal atomic structure.

Ballerini noted that thanks to graphene’s electrical properties, transparency, and flexibility, the material has become the ideal material candidate for several ongoing researches. Among these studies, the primary goal has been to analyze and investigate how graphene can tune neuronal excitability, as well as to demonstrate that the material can selectively modify membrane-associated neuronal functions. Ballerini and her team’s latest research, for one, operated under the hypothesis that there would be specific interactions between graphene and potassium ions in the extracellular solution which would regulate cell excitability.

“Graphene properties might (thus) affect neuronal information processing through the physical interactions of such a nanomaterial with the biological environment. Nanomaterials might then represent, in general, unconventional tools to gain insights into genuine biological processes,” Ballerini’s team stated in their conclusion to the recent study. 

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Ballerini and her team’s research could be accessed here.

The applications of graphene are wide, from practical solutions such as water filtration systems and faster internet speeds to measuring brain activity. The material, if any, seems to be tailor-fit for Elon Musk’s neurotechnology startup, Neuralink, which aims to create brain-computer interface systems. Considering that the startup is aimed at developing neural lace technologies, advances in graphene, showcased in these recent studies, could very well help make Musk’s vision of “wizard hats for the brain” a reality.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Elon Musk

Elon Musk rips ABC News over fatal NYC Tesla crash report

Musk pushed back on NYC Tesla crash coverage, pointing to a pattern of premature blame.

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Elon Musk pushed back overnight against media framing of a fatal Tesla crash in Midtown Manhattan, telling a user on X that “it wasn’t the car” and that the vehicle’s Autopilot system had nothing to do with the wreck.

The crash happened just before 3 a.m. Wednesday, when a 2024 Tesla Model Y struck a sidewalk shed outside 315 Madison Ave., a bus stop pole and a mailbox on East 42nd Street, according to the NYPD. The car kept moving several more blocks before stopping near Second Avenue. Both women inside, each 27, were taken to Bellevue Hospital, where the passenger was pronounced dead. The driver was charged with vehicular manslaughter, driving while ability impaired and leaving the scene of an accident.

Police have not attributed the crash to Autopilot or Full Self-Driving in any public statement. The charges point to impairment, not software. Musk’s response followed a since-deleted ABC News post that he said mischaracterized the incident. Replying to a user on X, Musk wrote that if Autopilot had been engaged, “they would not have crashed,” and added that “the legacy media will never forgive Tesla for failing to advertise with them,”

It’s a familiar cycle for Tesla. In June, headlines from several national outlets described a fatal crash in Katy, Texas, as happening while the car was “on autopilot,” based on the driver’s own account to police after his Model 3 struck a home and killed a 76-year-old woman. Tesla’s data told a different story when Ashok Elluswamy, Tesla’s head of AI, said the driver had pressed the accelerator to 100% and reached 73 mph in a residential zone. Harris County prosecutors later confirmed the human override and the driver was charged with manslaughter.

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Florida Gov. Ron DeSantis pointed to that same Katy crash last month to argue that outlets routinely name Tesla in crash headlines while leaving other automakers unnamed, even after a driver’s own actions are shown to be the cause. A similar pattern played out in 2024, when Musk had to clarify that FSD was never even downloaded onto the Model 3 involved in a fatal Colorado DUI crash, despite a passenger’s claim that an “auto drive feature” was in use.

Tesla has not issued a separate statement on the Manhattan crash beyond Musk’s posts on X. The NYPD’s investigation is ongoing, and no cause for the driver losing control has been released.

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Tesla’s two defunct flagship models are getting a big upgrade

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Tesla’s two recently-defunct flagship models, the Model S and Model X, are getting a big upgrade, according to the company’s Head of AI, Ashok Elluswamy.

Older Hardware 3 Model S and Model X vehicles have been the last major holdouts in Tesla’s Full Self-Driving v14 Lite rollout, and that wait now appears to be ending.

Tesla brings closure to flagship ‘sentimental’ models, Musk confirms

At Tesla’s Cybercab launch, AI chief Ashok Elluswamy told Ryan McCaffrey that he thought the S and X build “was supposed to go out last week.” Evidently, Elluswamy expects the suite to be rolled out to those HW3 Model S and Model X very soon:

Those cars are not the current Model S and Model X, which already ship with Hardware 4. They are the pre-refresh flagships built around Tesla’s older Autopilot computer, often called HW3 or AI3.

Tesla stopped putting that computer in new vehicles years ago, which is why owners treat these S and X cars as a closed generation. Model 3 and Model Y vehicles on the same computer began receiving v14 Lite in late June 2026 and saw a wider North American expansion in July. South Korea followed as an early international market. The S and X versions of the same software never joined that wave.

v14 Lite is Tesla’s way of squeezing the current v14 driving stack onto hardware that cannot run the full AI 4 model. The company describes the process as distillation: behaviors learned on the newer computer, including reinforcement learning and offline models, are compressed so the older chip and cameras can use them as a guide.

Early descriptions put the distilled network at roughly 15 percent of the original size. The result is still supervised Level 2 driving. Tesla has been clear that HW3 cannot support unsupervised Full Self-Driving or robotaxi operation because of memory and bandwidth limits.

The feature list is what made the wait so frustrating for S and X owners, as plenty of new features are to be shipped with it.

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Official notes for the first Lite build, firmware 2026.20.5.1, added parking, unparking, and reversing; arrival options for a parking lot, street, driveway, or curbside; speed profiles that stay available at all times; and start-from-park engagement. Tesla also claimed better handling of merges, forks, pedestrians, traffic lights, and cut-ins, plus fewer false slowdowns and smoother lane centering.

A mid-July follow-on build, 2026.20.6.10, added more of the Hardware 4 interface, including a standalone Self-Driving app and the ability to start a trip from Park without a brake-pedal confirmation.

Elluswamy called that version the one “likely going to wide release.”

That wide release already reached most other HW3 cars in the United States and Canada. International timing still depends on regional validation and regulatory approval. For S and X owners, the remaining work appears to be model-specific validation rather than a new software stack.

There is no official Tesla changelog or build number for those two models yet, only Elluswamy’s offhand timeline. Some HW3 drivers who already have Lite report large gains over v12.6; others have described new indecision or phantom braking. The next test will be whether the same software lands cleanly on the older flagships that have waited the longest.

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This tiny Tesla Cybertruck adjustment has big advantages

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Credit: Wes Morrill | X

Yesterday, we reported on Tesla Cybertruck getting some major adjustments from a manufacturing standpoint in an effort to make the all-electric pickup more cost-effective, more reliable, more serviceable, and more easily produced.

Tesla Cybertruck engineer reveals new changes in ‘constantly evolving’ pickup

One of those changes was the addition of a self-reinforcing polypropylene aero shield that sits underneath the truck. Previously, Tesla utilized aluminum for this, but the self-reinforcing polypropylene was more durable while also being cheaper and lighter.

Tesla has revealed another small change it made to the Cybertruck, and it has to do with the side repeater cameras.

Tesla does not wait for a new model year to improve its vehicles. On September 8, Cybertruck lead engineer Wes Morrill posted side-by-side photos of an updated side repeater camera housing now rolling off the line at Gigafactory Texas.

The triangular camera pod mounted on the front fender looks almost identical at first glance. A closer look reveals a revised contour that uses the air already flowing around the truck to keep the lens clearer in rain and road spray.

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The side repeater cameras sit in an exposed position on the Cybertruck’s angular stainless-steel body.

In wet weather, they readily collect water droplets that can degrade the image Autopilot and Full Self-Driving use for lane changes and blind-spot monitoring. Early production trucks sometimes left owners wiping lenses by hand or accepting temporary restrictions on driver-assistance features.

Tesla has added washers to cameras on certain other models and on Cybercab prototypes, but those active systems add cost, complexity, and extra potential leak points.

The new housing solves the problem with passive geometry. Subtle changes in the surround create localized airflow disturbances as the vehicle moves. Those eddies physically push water droplets away from the optical surface. Morrill called the result “pure vision improvement” achieved at “no cost penalty.” Once the production mold is updated, every subsequent part costs the same as the original.

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The advantages compound quickly. Clearer cameras in rain improve the reliability of driver-assistance features precisely when they are needed most. The design consumes no extra energy and introduces no new failure modes.

New Cybertrucks built after the tooling changeover receive the updated part automatically. Some owners of trucks delivered as late as June 2026 have already confirmed they received the revised housing. Retrofit questions have appeared in replies, and the cameras appear electrically compatible, though Tesla has not announced an official service program.

A few millimeters of reshaped housing will not make headlines the way a new battery pack does, but these changes are incremental and increase the Cybertruck’s effectiveness as a vehicle over time.

This improvement illustrates how Tesla continues to refine the Cybertruck after volume production began. Better wet-weather vision, zero added cost, and no extra hardware add up to a meaningful gain in everyday usability and safety.

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