Tech & AI

Känsliga leror förändrar bärförmåga vid temperaturväxlingar — en egenskap som konstruktörer hittills inte kunnat modellera tillräckligt väl. Forskare vid Chalmers University of Technology har utvecklat en termisk version av Creep-SClay1S-modellen som förutser hur temperaturförändringar påverkar lermas skenbara förkonsolideringstryck. Modellen bygger på omfattande laboratorieprov med endimensionell kompression på både omörkad och intakt naturlig lera. Jämfört med den isotermiska varianten ger den termiska modellen mest förbättrad noggrannhet för naturlig lera under effektivspänningar nära förkonsolideringstrycket — exakt det intervall som är operativt i geoteknisk konstruktion. Det effektivspänningsbaserade tillvägagångssättet möjliggör integration i befintliga multifysik-ramverk och öppnar vägen för termisk konsolidering. För energifundament och temperaturberoende grundläggningsproblem blir detta kritiskt för dimensioneringsäkerhet och prediktiv modellering.

Organiska solceller når nu 20,5% verkningsgrad genom en ny molekylär designmetod som stabiliteter acceptormaterial. Forskare vid Central South University konstruerade en bikristallin struktur genom att kombinera det etablerade acceptormaterialet L8-BO med en ny bensotriasolbaserad molekyl, Y18-C3. Båda materialens likartade konjugerade ryggrader möjliggör stark intermolekylär elektronisk koppling och utgör grunden för att finjustera energinivåer och ljusabsorption. Denna krystalinstrukturföstering reducerade rekombination av laddningsbärare markant. Systemet visar robusthet: även vid 50 procent Y18-C3-innehål uppnår cellerna över 19,6% verkningsgrad, vilket indikerar låg känslighet för sammansättningsvariationer i tillverkningen. För leverantörer av solcellsmaterial och tillverkare ligger relevansen i att denna designprincip möjliggör högre prestanda utan att kräva nya produktionslinjer. Linköping University och kinesiska universitet tillsammans stärker materialforskningen i detta område.

Researchers identified unique patterns of lipids and metabolites in dengue patients' blood that differ sharply from healthy people. The discovery could enable faster, more accurate diagnostic tests and reveal how the virus evades immune defenses—critical for developing treatments in a region where dengue infects 100+ million people annually.EN

Researchers have created a computational tool that accurately forecasts how trees and hedges will grow over time—and how much carbon they'll absorb. The model, tested on European forestry data, could help urban planners and developers make smarter decisions about green infrastructure investments and meet climate targets more reliably.EN

A new study shows European paper mills could become major carbon removal facilities, capturing 50 million tons of CO2 annually through existing technology. But toxic compounds in mill exhaust threaten to corrode equipment and degrade solvents, forcing researchers back to the lab before the industry can scale up.EN

Researchers have developed a drone-based system that sees through fog to detect ships and assess navigability in low-visibility shipping lanes—a capability that could reduce accidents and delays in critical maritime corridors. The technology combines AI vision with physics models to generate real-time safety scores, potentially reshaping operations for port authorities and shipping companies.EN

Researchers discovered that surface tension in molten steel actually increases above boiling temperature—defying conventional physics assumptions. The finding could improve manufacturing processes for casting, welding, and metal processing where extreme heat conditions are routine.EN

Researchers have developed an automated tuning method that improves pressure control in centrifugal fans—critical equipment in HVAC, manufacturing, and industrial processes. The hybrid optimization approach converges faster and reduces performance variability compared to conventional methods, potentially lowering energy costs and maintenance demands across facilities management and industrial operations.EN

Researchers have improved a mathematical bound that describes how fast certain algebraic structures can expand—a problem relevant to computational complexity and data structure design. The finding refines decades-old limits, potentially informing how engineers optimize algorithms and systems that depend on predictable growth rates.EN

Researchers analyzing two decades of bridge management research identified artificial intelligence, digital twins, and machine learning as the field's fastest-growing priorities. The findings matter because aging infrastructure worldwide demands smarter maintenance strategies—and companies and agencies investing in these technologies now could gain competitive advantages in a sector facing mounting safety and cost pressures.EN

Researchers developed a new framework that lets drones automatically decide what to observe and communicate in real-time, reducing both control and sensing expenses. The approach could reshape how autonomous systems manage limited battery and bandwidth — critical economics for commercial drone operators and 6G infrastructure planners.EN

Researchers have developed a Bayesian approach that uses AI-generated priors to reconstruct scrambled signals from significantly fewer noisy observations than existing methods require. The breakthrough could accelerate medical imaging analysis, particularly in cryo-electron microscopy, by reducing data collection costs and processing time—a major efficiency gain for labs and biotech companies relying on these techniques.EN

Researchers have built a text-to-speech system that begins speaking from the first word with near-imperceptible delay—a breakthrough for real-time applications like live translation and voice assistants. The technology achieves this speed without requiring massive datasets, matching quality of larger systems trained on far more data.EN

A new study reveals that standard bias benchmarks for speech AI systems don't reliably forecast how those same models behave in practical applications. The finding threatens the validity of current fairness testing methods and suggests companies and regulators may be relying on flawed metrics to assess AI safety.EN

Researchers have developed mathematical tools to predict worst-case scenarios in AI decision-making systems—the rare failures that standard performance metrics miss. The work matters because autonomous systems in healthcare, finance, and autonomous vehicles need guarantees about tail risks, not just average performance.EN

Researchers have developed a technique that lets vision-language AI systems adapt to new environments without requiring explicit domain information — a major hurdle in real-world deployment. The approach automatically discovers hidden patterns in training data, enabling more robust and flexible models that could reduce costly retraining cycles across industries.EN

Wearable energy trackers significantly misalign with how people with disabilities actually experience their bodies, according to new research. The disconnect matters for tech companies designing wellness products—most devices ignore fluctuations from illness, travel, and menstrual cycles, limiting their utility and forcing users to abandon or distrust the tools.EN

Showing users how algorithms pick ads for news articles makes them less likely to click—even when they trust the match more. The finding, based on 498 users, suggests companies face a tradeoff: transparency can undermine engagement, forcing businesses to choose between trust-building and conversion.EN

Researchers have cracked a fundamental problem in how particles arrange themselves when trapped in bounded areas—work with implications for materials science, quantum computing, and optimization algorithms. The breakthrough connects abstract mathematical theory to practical physical systems, potentially improving how engineers design constraints for particle-based technologies.EN

Researchers have solved a long-standing technical problem: how to let autonomous systems use multiple communication styles simultaneously without creating conflicts or interference. The advancement could accelerate deployment of multi-agent AI in manufacturing, logistics, and autonomous vehicle fleets where different robots need to coordinate using different protocols.EN

Researchers have created BUD-MI, a data collection framework that makes it easier for companies and cities to track how much material goes into buildings—crucial information for circular economy planning. The tool combines standardized templates with automated analysis, letting construction firms and policymakers understand material stocks without expensive, time-consuming surveys.EN

Researchers have demonstrated a novel two-layer heat storage system that captures and releases energy at temperatures up to 600°C with minimal losses, potentially solving a critical bottleneck in renewable energy adoption. The breakthrough could enable power grids to store excess solar and wind output for later use, reducing the need for expensive backup fossil fuel plants.EN

Scientists have released ARpest, free software that automates complex analysis of electronic materials without requiring coding skills. The tool could accelerate discovery in semiconductors, quantum materials, and energy tech by letting researchers focus on experiments rather than data processing.EN

Researchers have developed a machine learning method that significantly reduces the amount of labeled data needed to group similar items—a fundamental task in recommendation systems, customer segmentation, and search engines. The breakthrough addresses a critical bottleneck: training AI models when no initial comparison data exists, potentially cutting implementation costs for companies deploying clustering systems.EN

Researchers have developed a method to make PageRank—the algorithm that powers how search engines and content platforms score importance—fairer to underrepresented sources. As AI transparency becomes a regulatory priority, the work offers a practical tool for companies managing large networks to ensure their ranking systems don't systematically disadvantage certain groups or domains.EN