A Barcelona-based startup called Inbrain Neuroelectronics has produced a novel brain implant made of graphene and is gearing up for its first in-human test this summer.

The technology is a type of brain-computer interface. BCIs have garnered interest because they record signals from the brain and transmit them to a computer for analysis. They have been used for medical diagnostics, as communication devices for people who can’t speak, and to control external equipment, including robotic limbs. But Inbrain intends to transform its BCI technology into a therapeutic tool for patients with neurological issues such as Parkinson’s disease.

Because Inbrain’s chip is made of graphene, the neural interface has some interesting properties, including the ability to be used to both record from and stimulate the brain. That bidirectionality comes from addressing a key problem with the metallic chips typically used in BCI technology: Faradaic reactions. Faradaic reactions are a particular type of electrochemical processes that occurs between a metal electrode and an electrolyte solution. As it so happens, neural tissue is largely composed of aqueous electrolytes. Over time, these Faradaic reactions reduce the effectiveness of the metallic chips.

That’s why Inbrain replaced the metals typically used in such chips with graphene, a material with great electrical conductivity. “Metals have Faraday reactions that actually make all the electrons interact with each other, degrading their effectiveness...for transmitting signals back to the brain,” said Carolina Aguilar, CEO and cofounder of Inbrain.

Because graphene is essentially carbon and not a metal, Aguilar says the chip can inject 200 times as much charge without creating a Faradic reaction. As a result, the material is stable over the millions of pulses of stimulation required of a therapeutic tool. While Inbrain is not yet testing the chip for brain stimulation, the company expects to reach that goal in due time.

The graphene-based chip is produced on a wafer using traditional semiconductor technology, according to Aguilar. At clean-room facilities, Inbrain fabricates a 10-micrometer-thick chip. The chip consists of what Aguilar terms “graphene dots” (not to be confused with graphene quantum dots) that range in size from 25 to 300 micrometers. “This micrometer scale allows us to get that unique resolution on the decoding of the signals from the brain, and also provides us with the micrometric stimulation or modulation of the brain,” added Aguilar.

Testing the Graphene-Based BCI

The first test of the platform in a human patient will soon be performed at the University of Manchester, in England, where it will serve as an interface during the resection of a brain tumor. When resecting a tumor, surgeons must ensure that they don’t damage areas like the brain’s language centers so the patient isn’t impaired after the surgery. “The chip is positioned during the tumor resection so that it can read, at a very high resolution, the signals that tell the surgeon where there is a tumor and where there is not a tumor,” says Aguilar. That should enable the surgeons to extract the tumor with micrometric precision while preserving functional areas like speech and cognition.

Aguilar added, “We have taken this approach for our first human test because it is a very reliable and quick path to prove the safety of graphene, but also demonstrate the potential of what it can do in comparison to metal technology that is used today.”

Aguilar stresses that the Inbrain team has already tested the graphene-based chip’s biocompatibility. “We have been working for the last three years in biocompatibility through various safety studies in large animals,” said Aguilar. “So now we can have these green lights to prove an additional level of safety with humans.”

While this test of the chip at Manchester is aimed at aiding in brain tumor surgery, the same technology could eventually be used to help Parkinson’s patients. Toward this aim, Inbrain’s system was granted Breakthrough Device Designation last September from the U.S. Food & Drug Administration as an adjunctive therapy for treating Parkinson’s disease. “For Parkinson’s treatment, we have been working on different preclinical studies that have shown reasonable proof of superiority versus current commercial technology in the [reduction] of Parkinson’s disease symptoms,” said Aguilar.

For treating Parkinson’s, Inbrain’s chip connects with the nigrostriatal pathway in the brain that is critical for movements. The chip will first decode the intention message from the brain that triggers a step or the lifting of the arm—something that a typical BCI can do. But Inbrain’s chip, with its micrometric precision, can also decode pathological biomarkers related to Parkinson’s symptoms, such as tremors, rigidity, and freezing of the gait.

By determining these biomarkers with great precision, Inbrain’s technology can determine how well a patient’s current drug regimen is working. In this first iteration of the Inbrain chip, it doesn’t treat the symptoms of Parkinson’s directly, but instead makes it possible to better target and reduce the amount of drugs that are used in treatment.

“Parkinson’s patients take huge amounts of drugs that have to be changed over time just to keep up with the growing resistance patients develop to the power of the drug,” said Aguilar. “We can reduce it at least 50 percent and hopefully in the future more as our devices become precise.”

Quantum computing is a devilishly complex technology, with many technical hurdles impacting its development. Of these challenges two critical issues stand out: miniaturization and qubit quality.

IBM has adopted the superconducting qubit road map of reaching a 1,121-qubit processor by 2023, leading to the expectation that 1,000 qubits with today’s qubit form factor is feasible. However, current approaches will require very large chips (50 millimeters on a side, or larger) at the scale of small wafers, or the use of chiplets on multichip modules. While this approach will work, the aim is to attain a better path toward scalability.

Now researchers at MIT have been able to both reduce the size of the qubits and done so in a way that reduces the interference that occurs between neighboring qubits. The MIT researchers have increased the number of superconducting qubits that can be added onto a device by a factor of 100.

“We are addressing both qubit miniaturization and quality,” said William Oliver, the director for the Center for Quantum Engineering at MIT. “Unlike conventional transistor scaling, where only the number really matters, for qubits, large numbers are not sufficient, they must also be high-performance. Sacrificing performance for qubit number is not a useful trade in quantum computing. They must go hand in hand.”

The key to this big increase in qubit density and reduction of interference comes down to the use of two-dimensional materials, in particular the 2D insulator hexagonal boron nitride (hBN). The MIT researchers demonstrated that a few atomic monolayers of hBN can be stacked to form the insulator in the capacitors of a superconducting qubit.

Just like other capacitors, the capacitors in these superconducting circuits take the form of a sandwich in which an insulator material is sandwiched between two metal plates. The big difference for these capacitors is that the superconducting circuits can operate only at extremely low temperatures—less than 0.02 degrees above absolute zero (-273.15 °C).

Superconducting qubits are measured at temperatures as low as 20 millikelvin in a dilution refrigerator.Nathan Fiske/MIT

In that environment, insulating materials that are available for the job, such as PE-CVD silicon oxide or silicon nitride, have quite a few defects that are too lossy for quantum computing applications. To get around these material shortcomings, most superconducting circuits use what are called coplanar capacitors. In these capacitors, the plates are positioned laterally to one another, rather than on top of one another.

As a result, the intrinsic silicon substrate below the plates and to a smaller degree the vacuum above the plates serve as the capacitor dielectric. Intrinsic silicon is chemically pure and therefore has few defects, and the large size dilutes the electric field at the plate interfaces, all of which leads to a low-loss capacitor. The lateral size of each plate in this open-face design ends up being quite large (typically 100 by 100 micrometers) in order to achieve the required capacitance.

In an effort to move away from the large lateral configuration, the MIT researchers embarked on a search for an insulator that has very few defects and is compatible with superconducting capacitor plates.

“We chose to study hBN because it is the most widely used insulator in 2D material research due to its cleanliness and chemical inertness,” said colead author Joel Wang, a research scientist in the Engineering Quantum Systems group of the MIT Research Laboratory for Electronics.

On either side of the hBN, the MIT researchers used the 2D superconducting material, niobium diselenide. One of the trickiest aspects of fabricating the capacitors was working with the niobium diselenide, which oxidizes in seconds when exposed to air, according to Wang. This necessitates that the assembly of the capacitor occur in a glove box filled with argon gas.

While this would seemingly complicate the scaling up of the production of these capacitors, Wang doesn’t regard this as a limiting factor.

“What determines the quality factor of the capacitor are the two interfaces between the two materials,” said Wang. “Once the sandwich is made, the two interfaces are “sealed” and we don’t see any noticeable degradation over time when exposed to the atmosphere.”

This lack of degradation is because around 90 percent of the electric field is contained within the sandwich structure, so the oxidation of the outer surface of the niobium diselenide does not play a significant role anymore. This ultimately makes the capacitor footprint much smaller, and it accounts for the reduction in cross talk between the neighboring qubits.

“The main challenge for scaling up the fabrication will be the wafer-scale growth of hBN and 2D superconductors like [niobium diselenide], and how one can do wafer-scale stacking of these films,” added Wang.

Wang believes that this research has shown 2D hBN to be a good insulator candidate for superconducting qubits. He says that the groundwork the MIT team has done will serve as a road map for using other hybrid 2D materials to build superconducting circuits.