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Category: computing – Page 7

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 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– that can mimic neuron-like 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 (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, 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 ).

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.

Meta’s new ultra-thin flat-panel display could change the future of screens

Meta has developed a new flat ultra-thin panel laser display that could lead to lighter, more immersive augmented reality (AR) glasses and improve the picture quality of smartphones, tablets and televisions. The new display is only two millimeters thick and produces bright, high-resolution images.

Flat-panel displays, particularly those illuminated by LEDs, are ubiquitous, seen in everything from smartphones and televisions to laptops and computer monitors. But no matter how good the current technology is, the search for better is always ongoing. Lasers promise superior brightness and the possibility of making the technology smaller and more energy efficient by replacing bulky and power-hungry components with compact -based ones.

However, current laser displays still need large, complex optical systems to shine light onto screens. Previous attempts at making flat-panel laser displays have come up short as they required complex setups or were too difficult to manufacture in large quantities.

Turning spin loss into energy: New principle could enable ultra-low power devices

A research team has developed a device principle that can utilize “spin loss,” which was previously thought of as a simple loss, as a new power source for magnetic control.

The work is published in the journal Nature Communications.

Spintronics is a technology that utilizes the “spin” property of electrons to store and control information, and it is being recognized as a key foundation for next-generation information processing technologies such as ultra-low-power memory, neuromorphic chips, and computational devices for stochastic computation, as it consumes less power and is more nonvolatile than conventional semiconductors.

Cell-mapping tool provides insightful multi-layered view of cancer behavior

Researchers at VCU Massey Comprehensive Cancer Center have developed a new computational tool called Vesalius, which could help clinicians understand the complex relationships between cancer cells and their surrounding cells, leading to potential discoveries regarding the development of hard-to-treat cancers.

Findings from a new study, published in Nature Communications, could help guide the identification of predictive biomarkers for multiple cancers and better inform the effectiveness of different treatment options based on individuals’ specific type of disease.

Rajan Gogna, Ph.D., member of the Developmental Therapeutics research program at Massey and assistant professor in the VCU School of Medicine’s Department of Human and Molecular Genetics, and a team of collaborators were driven by the goal of interpreting extensive amounts of data in a meaningful way.

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