Integrated circuits are the brains behind modern electronic devices like computers or smart phones. Traditionally, these circuits—also known as chips—rely on electricity to process data. In recent years, scientists have turned their attention to photonic chips, which perform similar tasks using light instead of electricity to improve speed and energy efficiency.
Electrons can be elusive, but Cornell researchers using a new computational method can now account for where they go—or don’t go—in certain layered materials.
Physics and engineering researchers have confirmed that in certain quantum materials, known as “misfits” because their crystal structures don’t align perfectly—picture LEGOs where one layer has a square grid and the other a hexagonal grid—electrons mostly stay in their home layers.
This discovery, important for designing materials with quantum properties including superconductivity, overturns a long-standing assumption. For years, scientists believed that large shifts in energy bands in certain misfit materials meant electrons were physically moving from one layer to the other. But the Cornell researchers have found that chemical bonding between the mismatched layers causes electrons to rearrange in a way that increases the number of high-energy electrons, while few electrons move from one layer to the other.
In the next section, we’ll look at the ways scientists can grow nanowires from the bottom up.
Looking at the Nanoscale.
A nanoscientist’s microscope isn’t the same kind that you’ll find in a high school chemistry lab. When you get down to the atomic scale, you’re dealing with sizes that are actually smaller than the wavelength of visible light. Instead, a nanoscientist could use a scanning tunneling microscope or an atomic force microscope. Scanning tunneling microscopes use a weak electric current to probe the scanned material. Atomic force microscopes scan surfaces with an incredibly fine tip. Both microscopes send data to a computer, which assembles the information and projects it graphically onto a monitor.
Developing an advanced Brain-Computer Interface (BCI) is only the beginning.
“In order to prove a theory of consciousness is right, you have to see it for yourself,” Hodak explains. “That will require these big brain-computer interfaces.”
Hodak thinks that once humans understand how billions of neurons bind together to create a unified experience — what neuroscientists call “the binding problem” — we can start doing truly wild things.
I almost hesitate to say some of those wild things include multiple brains working to form one consciousness. “You could really, in a very fundamental sense, talk about redrawing the border around a brain, possibly to include four hemispheres, or a device, or a whole group of people,” he says.
With its largest advancement since the NVIDIA CUDA platform was invented in 2006, CUDA 13.1 is launching NVIDIA CUDA Tile. This exciting innovation introduces a virtual instruction set for tile-based parallel programming, focusing on the ability to write algorithms at a higher level and abstract away the details of specialized hardware, such as tensor cores.
CUDA exposes a single-instruction, multiple-thread (SIMT) hardware and programming model for developers. This requires (and enables) you to exhibit fine-grained control over how your code is executed with maximum flexibility and specificity. However, it can also require considerable effort to write code that performs well, especially across multiple GPU architectures.
There are many libraries to help developers extract performance, such as NVIDIA CUDA-X and NVIDIA CUTLASS. CUDA Tile introduces a new way to program GPUs at a higher level than SIMT.
Researchers at UC Santa Barbara have invented a display technology for on-screen graphics that are both visible and haptic, meaning that they can be felt via touch.
The screens are patterned with tiny pixels that expand outward, yielding bumps when illuminated, enabling the display of dynamic graphical animations that can be seen with the eyes and felt with the hand. This technology could one day enable high-definition visual-haptic touch screens for automobiles, mobile computing or intelligent architectural walls.
Max Linnander, a Ph.D. candidate in the RE Touch Lab of mechanical engineering professor Yon Visell, led the research, which appears in the journal Science Robotics.