Even if you only keep a loose watch on tech news, there’s still a pretty good chance you’ve heard about graphene at some point or another. For the past few years, this stuff (which is basically a 2D sheet of carbon atoms) has been hailed as a wonder material that will one day enable us to build everything from superfast computer chips to unbreakable condoms, and everything in between.
The only problem? It’s notoriously difficult to manufacture in large quantities. Scientists have developed a number of different lab production techniques, ranging from the incredibly complex to the unbelievably simple, but despite all the research going on in this area, nobody has really devised a viable way to mass produce graphene — until now.
Detailed in a recently-published study in Scientific Reports, a team of researchers from MIT and the University of Michigan have cooked up a new method for continuous production of graphene — a process that could finally bring the exotic material out of the lab and into all the high-flying commercial applications we’ve been dreaming about for the past few years.
The new technique is essentially a more refined version of a widely used lab synthesis method known as chemical vapor deposition (CVD). In a nutshell, CVD involves (in the case of graphene) pumping carbon-laden vapor into a vacuum chamber, where it reacts with a substrate (usually a sheet of copper foil) and forms a thin film. The new system utilizes a very similar vapor chemistry — but instead of depositing the carbon onto a static sheet, it deposits it onto a copper ribbon, which is perpetually spooled through the chamber.
It’s a bit more complex than that, but essentially, the pioneering new technique makes it possible to create a continuous, unbroken ribbon of graphene. Because the process is continuous, it eliminates the need to stop and start the machine to permit graphene sheets to be unloaded, as is currently required by today’s batch manufacturing processes. This is a big development, as it could lead to a significant scale-up of graphene production, and finally make the material cheaper and more widely available.
The technique is still in its infancy, and the graphene it produces isn’t quite perfect, but the team is already working on ways to improve both quality and production speed. Once they’ve worked out all the kinks in the process, the next step will be to push the limits and make the process even faster.
San Francisco startup Dimensional advertised for people to walk robot dogs through city streets. The New York Times reported that the job could include carrying a roughly 33-pound robot back to the office if it overheated. A lift home is an awkward requirement for a labor-saving machine.
Keeping the hardware running is only one challenge. Anthropic's robotics tests found that language models mostly failed when controlling joints directly, but did better when directing trained controllers. Giving an AI agent a body doesn't teach it to handle ordinary household objects.
Soon, a mattress protector may be more than a bed cover. Australian medtech company Sleeptite and researchers at RMIT University have received a US patent for FlexiSense, a smart bedding technology that tracks body position and posture to help caregivers identify when older residents may be at risk of falling.
The technology is being developed for Sleeptite’s in-bed monitoring system, REMi, and was recently on display at The MedTech Conference in Boston. A peer-reviewed study in Flexible and Printed Electronics says the sensors can also be made at scale without sacrificing performance or durability.
AI companies spend enormous amounts of time convincing us their technology is safe and secure. But what happens when those same companies become targets of increasingly sophisticated AI-powered attacks? Anthropic, the company behind Claude, is now facing that question. According to a Washington Post report, cybersecurity startup Cathedral discovered vulnerabilities that let its researchers access sensitive information in Anthropic's internal systems.
The researchers used AI agents to identify potential entry points in less than 12 hours. Interestingly, they didn't need to crack Claude itself. Instead, they exploited weaknesses in third-party business applications that Anthropic uses for everyday operations. Anthropic's security testing program disclosed the findings, which allows outside researchers to identify and report vulnerabilities.