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Category: computing

New topology-based biomarkers may improve breast cancer prediction

For decades, pathologists have diagnosed and graded breast cancer by looking at tissue samples under a microscope, searching for telltale signs of disorder in the structure of cells and tissues. Now, researchers at Columbia and their collaborators have developed a new computational approach that transforms those visual patterns into quantitative measurements, potentially improving how clinicians predict breast cancer outcomes and choose therapies.

In a recent study published in Cancer Research, researchers used mathematical tools known as topology to develop biomarkers quantifying the organizational structure of breast cancer tissue. The approach generated continuous numerical scores that predicted patient survival and treatment response more accurately than many traditional biomarkers, while also showing less variation across racial and ethnic groups.

Beyond lithium: how sodiumion batteries could change the world

The lithium-ion battery is the beating heart of the modern world. It powers eight billion mobile phones, hundreds of millions of laptops and rapidly growing fleets of electric cars and energy-storage banks. But there’s a new contender breaking into the battery market.

Batteries based on sodium promise to be cheaper, safer and much more environmentally friendly than lithium-ion cells. And this year could mark the start of the sodium era.

In April, Chinese firm CATL — the world’s largest battery producer — announced that it will start mass-producing sodium-ion batteries before the end of 2026. CATL, which is headquartered in Ningde, added that it had signed deals to sell the batteries both to a car manufacturer and to a provider of energy-storage stations for electricity grids.

Thinner wires, faster electrons: Quantum material challenges copper at chip scale

Electrical interconnects may very well be the unsung heroes of modern microchips. These tiny wires—typically made of copper due to its high conductivity—string together the billions of transistors that drive our computers and electronic devices. But as the technology advances and additional transistors are piled on, the components must shrink to the nanoscale. And that’s when copper begins to fail.

Cornell researchers have developed a potential replacement for copper interconnects: single-crystal nanowires of niobium arsenide. This topological semimetal paradoxically becomes a better conductor the thinner it gets, boosting electronic performance.

The findings were published July 16 in Science. The lead author is doctoral student Yeryun Cheon. Judy Cha, the Rick and Betty Tsai Ph.D. 1981 Professor in Materials Science and Engineering in the Cornell Duffield College of Engineering, is the paper’s senior author.

Dendrites may be key to learning and memory, study suggests

Branchlike structures called dendrites that extend from neurons appear to make their own computations independent of the cell body, helping individual brain cells store memories of the past, respond to the present and anticipate the future, a study led by UT Southwestern Medical Center researchers suggests.

The findings, published in Science, represent a paradigm shift in current models of how learning and memory take place.

“This shifts our entire perspective. Rather than acting as simple switches, neurons behave more like sophisticated processors with internal divisions of labor, dramatically increasing the brain’s computational capacity,” said Attila Losonczy, M.D., Ph.D., professor at the Peter O’Donnell Jr. Brain Institute of Neuroscience and director of the Program in Memory Longevity (PML) at UT Southwestern.

Brain-inspired nanopore device uses current-induced heating for memory operations

Some researchers are leaning into biology for inspiration in computing. In particular, neuromorphic computing offers a brain-inspired approach to hardware that replaces traditional binary processing with systems that function more like neurons and synapses. Now, a new study, published in Nature Communications, describes an innovative design for a fluidic memristor that uses its own self-heating mechanism to induce a history-dependent memory effect.

So far, most memristor (memory resistor) devices have used solid materials with electrons or holes functioning as charge carriers. But fluidic memristors instead take advantage of the movement of ions in liquids, which more closely mimics biological signaling, like that which occurs in the brain. However, existing fluidic memristors can be difficult to fabricate and offer a limited range of memory behaviors. The authors of the new study came up with a way to overcome some of these limitations by using temperature fluctuations while also making the device more “brain-like.”

They write, The exploration of additional memristive mechanisms may be beneficial. In conventional integrated circuits, localized heating is generally regarded as an unnecessary and even harmful side effect. However, in biological neural systems, thermal signals are closely linked to essential life processes. They significantly affect neuronal functions, including ion channel activation, action potential conduction speed, and firing patterns.

Engineers shrink powerful terahertz systems onto a single semiconductor chip

High-frequency waves classified as terahertz occupy a relatively underused region of the electromagnetic spectrum between infrared light and microwaves. Researchers have long recognized their unique potential for applications including ultrafast wireless communication, security screening, remote sensing and medical imaging.

As technologies push toward higher operating frequencies and data rates, photonics-based terahertz systems, which use light at high speed to generate and process terahertz signals, have emerged as a promising alternative to conventional electronic technologies because of their superior bandwidth and power efficiency. However, today’s terahertz optoelectronic systems, which are electronic systems that control light, remain bulky, complex and difficult to scale for widespread use. They typically rely on multiple separate components—including lasers, amplifiers, modulators, sources and detectors—that must be individually made, aligned and interconnected, limiting their use outside specialized laboratory settings.

Now, a UCLA–led research team has demonstrated a way to integrate these functions onto a single semiconductor chip compatible with modern photonic technologies. The breakthrough, published in Nature Communications, paves the way for compact, scalable terahertz systems for next-generation communication, imaging and sensing applications.

A new ‘library’ for Feynman integrals

Theoretical physicists at Johannes Gutenberg University Mainz (JGU) have developed a new method of ordering Feynman integrals. This critical step in making theoretical predictions for high-energy precision measurements has posed a major computational bottleneck until now.

Scientists in the research group of Professor Stefan Weinzierl from the PRISMA⁺⁺ Cluster of Excellence propose a solution to this longstanding challenge in new articles published in Physical Review Letters and Physical Review D. By ordering the integrals according to their intrinsic geometric properties, they can speed computation times by a factor of about 1,000.

“Feynman integrals are mathematical expressions that researchers must evaluate to make precise predictions,” said Weinzierl. “These are the first pillars for precise predictions for measurements at facilities like the Large Hadron Collider in Switzerland.” The number of these integrals varies from process to process, with some processes needing up to one million.

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