Quantum computers promise enormous computational power, but the nature of quantum states makes computation and data inherently “noisy.” Rice University computer scientists have developed algorithms that account for noise that is not just random but malicious. Their work could help make quantum computers more accurate and dependable.
Researchers at Beijing Genomics and IMDEA Nanociencia institutes have introduced a novel method that could significantly accelerate efficiency and reduce the cost of handling fluidics in DNA sequencing.
Traditional DNA sequencing relies on flow cells, where liquid reagents are repeatedly pumped in and out for each of the sequencing reactions. For large-scale sequencing, this process involves immersing silicon wafers into reagents—a method that works well at industrial scale but is impractical for smaller labs or clinical settings, where sample sizes are limited and drying effects become a problem.
The new approach turns that process on its head. Instead of pumping fluids through a chamber, the researchers use a roll-to-roll technique that gently shears the liquid across the surface. This dramatically improves efficiency, allowing reagents to be replaced more quickly and uses up to 85 times less material. As a result, DNA sequencing that once took days can now be completed in under 12 hours, with significantly lower reagent costs.
A new and powerful particle detector just passed a critical test in its goal to decipher the ingredients of the early universe. The sPHENIX detector is the newest experiment at Brookhaven National Laboratory’s Relativistic Heavy Ion Collider (RHIC) and is designed to precisely measure products of high-speed particle collisions.
A research team from Aarhus University, Denmark, has measured and explained the exceptionally low thermal conductivity of the crystalline material AgGaGe3Se8. Despite its ordered structure, the material behaves like a glass in terms of heat transport—making it one of the least heat-conductive crystalline solids known to date.
At room temperature, AgGaGe3Se8 exhibits a thermal conductivity of just 0.2 watts per meter-Kelvin—which is three times lower than water and five times lower than typical silica glass. The material is composed of silver (Ag), gallium (Ga), germanium (Ge), and selenium (Se), and has previously been studied for its optical properties.
Now, for the first time, researchers from iMAT—the Aarhus University Center for Integrated Materials Research—have measured its thermal transport properties and identified the structural origin of its unusually low thermal conductivity.
Researchers have demonstrated a new fabrication approach that enables the exploration of a broader range of superconducting materials for quantum hardware.
The study, published in Applied Physics Letters, addresses a long-standing challenge: many promising superconductors, such as transition metal nitrides, carbides, and silicides, are difficult to pattern into functional devices using conventional chemistry-based methods.
By showing that physical patterning provides a viable alternative, the study paves the way to evaluate and harness these materials for high-performing quantum technologies.
If your hand lotion is a bit runnier than usual coming out of the bottle, it might have something to do with the goop’s “mechanical memory.”
Soft gels and lotions are made by mixing ingredients until they form a stable and uniform substance. But even after a gel has set, it can hold onto “memories,” or residual stress, from the mixing process. Over time, the material can give in to these embedded stresses and slide back into its former, premixed state. Mechanical memory is, in part, why hand lotion separates and gets runny over time.
Now, an MIT engineer has devised a simple way to measure the degree of residual stress in soft materials after they have been mixed, and found that common products like hair gel and shaving cream have longer mechanical memories, holding onto residual stresses for longer periods of time than manufacturers might have assumed.
The notion of a phased array was initially articulated by Nobel Prize recipient K. F. Braun. Phased arrays have subsequently evolved into a formidable mechanism for wave manipulation. This assertion holds particularly true in the realm of ultrasound, wherein arrays composed of ultrasound-generating transducers are employed in various applications, including therapeutic ultrasound, tissue engineering, and particle manipulation.
Importantly, these applications—contrary to those aimed at imaging—demand high-intensity ultrasound, which complicates the electrical driving requirements, as each channel necessitates its own independently operational pulse circuitry and amplifier. Consequently, the majority of phased array transducers (PATs) are constrained to several hundred elements, thereby restricting the capability to shape intricate ultrasound beams.
To date, there exists no scalable methodology for the powering and control of phased array transducers.
