This collection explores the intricate properties two-dimensional materials possess which hold immense potential for advancing neuromorphic computing.
Category: computing – Page 63
Caltech breakthrough makes quantum memory last 30 times longer
While superconducting qubits are great at fast calculations, they struggle to store information for long periods. A team at Caltech has now developed a clever solution: converting quantum information into sound waves. By using a tiny device that acts like a miniature tuning fork, the researchers were able to extend quantum memory lifetimes up to 30 times longer than before. This breakthrough could pave the way toward practical, scalable quantum computers that can both compute and remember.
MRI technology inspires quantum advancement with 2D materials
The same technology behind MRI images of injury or disease also powers nuclear magnetic resonance (NMR) spectroscopy, which is used to analyze biological molecules for research on diseases and therapeutics. While NMR spectroscopy produces valuable data about the structure of molecules, the resolution is too low to sense individual atoms.
Now, quantum researchers at Purdue University are advancing an approach that could improve the resolution of NMR spectroscopy to the atomic scale and may also have applications in developing quantum computing and quantum communications.
“Conventional NMR spectroscopy is limited to measuring large samples of molecules. We’re interested in developing technologies that can detect and analyze a single molecule,” said Tongcang Li, professor of physics and astronomy in the College of Science and of electrical and computer engineering in the College of Engineering.
Scientists just created spacetime crystals made of knotted light
Researchers have developed a blueprint for weaving hopfions—complex, knot-like light structures—into repeating spacetime crystals. By exploiting two-color beams, they can generate ordered chains and lattices with tunable topology, potentially revolutionizing data storage, communications, and photonic processing.
Electro-optical Mott neurons made of niobium dioxide created for brain-inspired computing
Over the past decades, engineers have introduced a wide range of computing systems inspired by the human brain or designed to emulate some of its functions. These include devices that artificially reproduce the behavior of brain cells (e.g., neurons), by processing and transmitting signals in the form of electrical pulses.
Most neuron-inspired devices developed so far use either electrons or photons to process and transmit information, rather than integrating the two. This is because photonic and electronic systems typically have very different architectures, and converting the signals they rely on can be challenging and lead to energy losses.
Researchers at Stanford University, Sandia National Laboratories, and Purdue University recently developed new electro–optical devices that can mimic neuron-like electrical pulses and simultaneously emit oscillating light. These devices, referred to as electro-optical Mott neurons, were introduced in a paper published in Nature Electronics.
Universal UltraRAM memory is one step closer to production: fast as DRAM and retains data for thousands of years
UltraRAM blurs the line between permanent and random access memory. Quinas Technology and IQE plc have developed the technology for scalable production.
Quinas Technology, the company behind UltraRAM, has been actively working with chipmaker IQE plc over the past year to scale UltraRAM production to industrial levels. According to Blocks & Files, еhe cooperation was successful, and a memory that promises speed, similar to DRAM and 4,000 times greater durability, than NAND, and data retention for up to a thousand years is now on the verge of production.
UltraRAM manufacturing is based on the epitaxy process. Complex semiconductor layers are grown with great precision on a crystal substrate. Later, more conventional semiconductor manufacturing processes such as photolithography and etching are used to create the structures of memory chips.
A promising approach for the direct on-chip synthesis of boron nitride memristors
Two-dimensional (2D) materials, thin crystalline substances only a few atoms thick, have numerous advantageous properties compared to their three-dimensional (3D) bulk counterparts. Most notably, many of these materials allow electricity to flow through them more easily than bulk materials, have tunable bandgaps, are often also more flexible and better suited for fabricating small, compact devices.
Past studies have highlighted the promise of 2D materials for creating advanced systems, including devices that perform computations emulating the functioning of the brain (i.e., neuromorphic computing systems) and chips that can both process and store information (i.e., in-memory computing systems). One material that has been found to be particularly promising is hexagonal boron nitride (hBN), which is made up of boron and nitrogen atoms arranged in a honeycomb lattice resembling that of graphene.
This material is an excellent insulator, has a wide bandgap that makes it transparent to visible light, a good mechanical strength, and retains its performance at high temperatures. Past studies have demonstrated the potential of hBN for fabricating memristors, electronic components that can both store and process information, acting both as memories and as resistors (i.e., components that control the flow of electrical current in electronic devices).
How to build larger, more reliable quantum computers, even with imperfect links between chips
While quantum computers are already being used for research in chemistry, material science, and data security, most are still too small to be useful for large-scale applications. A study led by researchers at the University of California, Riverside, now shows how “scalable” quantum architectures—systems made up of many small chips working together as one powerful unit—can be made.