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Researchers find graphene can strengthen the brain’s neural signals
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.
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.
Elon Musk
Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story
Tesla confirmed HW3 vehicles cannot run unsupervised FSD, replacing its free upgrade promise with a discounted trade-in.
Tesla has officially confirmed that early vehicles with its Autopilot Hardware 3 (HW3) will not be capable of unsupervised Full Self-Driving, while extending a path forward for legacy owners through a discounted trade-in program. The announcement came by way of Elon Musk in today’s Tesla Q1 2026 earnings call.
🚨 Our LIVE updates on the Tesla Earnings Call will take place here in a thread 🧵
Follow along below: pic.twitter.com/hzJeBitzJU
— TESLARATI (@Teslarati) April 22, 2026
The history here matters. HW3 launched in April 2019, and Tesla sold Full Self-Driving packages to owners on the understanding that the hardware was sufficient for full autonomy. Some owners paid between $8,000 and $15,000 for FSD during that period. For years, as FSD’s AI models grew more demanding, HW3 vehicles fell progressively further behind, eventually landing on FSD v12.6 in January 2025 while AI4 vehicles moved to v13 and then v14. When Musk acknowledged in January 2025 that HW3 simply could not reach unsupervised operation, and alluded to a difficult hardware retrofit.
The near-term offering is more concrete. Tesla’s head of Autopilot Ashok Elluswamy confirmed on today’s call that a V14-lite will be coming to HW3 vehicles in late June, bringing all the V14 features currently running on AI4 hardware. That is a meaningful software update for owners who have been frozen at v12.6 for over a year, and it represents genuine effort to keep older hardware relevant. Unsupervised FSD for vehicles is now targeted for Q4 2026 at the earliest, with Musk describing it as a gradual, geography-limited rollout.
For HW3 owners, the over-the-air V14-lite update is welcomed, and the discounted trade-in path at least acknowledges an old obligation. What happens next with the trade-in pricing will define how this chapter ultimately gets written. If Tesla prices the hardware path fairly, acknowledges what early adopters are owed, and delivers V14-lite on the June timeline it committed to today, it has a real opportunity to convert one of the longest-running sore subjects among early adopters into a loyalty story.
Elon Musk
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.
Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”
Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.
Credit: TESLA
Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.
As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.
As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.
Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.
Tesla Q1 2026 Earnings Results
Tesla’s Earnings Results are as follows:
- Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
- Revenues – $22.387 billion vs. $22.35 billion Expected
- Free Cash Flow – $1.444 billion
- Profit – $4.72 billion
Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.
On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.
Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q1 2026 Earnings Call at 4:30pm CT https://t.co/pkYIaGJ32y
— Tesla (@Tesla) April 22, 2026
Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
