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Aided eye: Neural network helps augment 3D micro-CT images of fibrous materials

Researchers from Skoltech and KU Leuven used machine learning to reconstruct 3D micro-CT images of fibrous materials, overcoming the difficulties faced by humans in analyzing these complex materials. The team employed GANs to fill a gap in available inpainting tools, enabling precise material analysis and simulation.

SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalComputational Materials Science·DateAug 18, 2021

Mathematical model of thermoplastic composite helps design and certify highly reliable structures

Researchers at Skoltech developed a mathematical model for thermoplastic composite materials, reducing conservatism in strength calculations. The model allows for virtual testing of structures, minimizing manufacturing costs while ensuring safety and quality requirements.

SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalInternational Journal of Pressure Vessels and Piping·DateAug 10, 2021

Building blocks: New evidence-based system predicts element combination forming high entropy alloy

Researchers developed a novel evidence-based material recommender system that predicts high entropy alloy formation without data descriptors, overcomes data bias and poor availability. The method recommends an FeMnCoNi alloy as the most probable HEA and successfully synthesizes it, confirming its validity.

SourceJapan Advanced Institute of Science and Technology·JournalNature Computational Science·TypeExperimental study·DateAug 4, 2021

Scientists obtain new polymer composite for electromagnetic shielding applications

Researchers from NUST MISIS and international partners create a radar-absorbing polymer composite with excellent magnetic and microwave properties. The composite can absorb 99.9% of incoming electromagnetic radiation, making it suitable for EMI shielding applications in industries such as 5G networks and radar absorbing coatings.

SourceNational University of Science and Technology MISIS·JournalJournal of Alloys and Compounds·DateJul 30, 2021

Programmable structures from the printer

Scientists have created movable, self-adjusting materials systems with complex shape changes that can be triggered by moisture. These systems mimic the movement mechanisms of the air potato plant and have produced their first prototype: a forearm brace that adapts to the wearer.

SourceUniversity of Freiburg·JournalAdvanced Science·DateJul 9, 2021

The bitumen puzzle

Researchers used AFM-IR, ToF-SIMS, and fluorescence microscopy to study bitumen surface composition and structure. The study found that the surface is heterogeneous, with individual molecular assemblies distributed in a specific pattern.

SourceVienna University of Technology·JournalScientific Reports·DateJul 6, 2021

How do good metals go bad?

Researchers found that exotic metallic materials exhibit poor electrical conductivity due to tiny amounts of impurities or defects. These defects cause electrons to remain localized, hindering current flow at low frequencies, but allowing it at high frequencies.

SourceVienna University of Technology·JournalNature Communications·DateMar 15, 2021

New insulation takes heat off environment

Researchers at Flinders University have developed a new sustainable insulation material using waste cooking oil, sulfur, and wool offcuts, offering promising energy savings for property owners and tenants. The composite boasts low flammability and biodegradable properties, aligning with the UN's Sustainable Development Goals.

SourceFlinders University·JournalChemSusChem·DateMar 12, 2021

Moiré than meets the eye

Carbon nanotubes have been engineered to produce moiré patterns, which could enhance material properties. The researchers' breakthrough has significant implications for the development of superconducting materials with improved performance.

SourceUniversity of Tokyo·JournalNature Communications·DateMar 10, 2021

Magnetic effect without a magnet

Researchers find giant Hall effect in material Ce3Bi4Pd3, exceeding theoretical predictions by a thousand times. The effect is caused by complex electron interactions and the Kondo effect, leading to unexpected potential for next-generation quantum technologies.

SourceVienna University of Technology·JournalProceedings of the National Academy of Sciences·DateFeb 22, 2021

Quickly identify high-performance multi-element catalysts

Researchers from Ruhr-Universität Bochum and University of Copenhagen developed an approach to predict optimal composition and confirm accuracy with high-throughput experiments. The strategy enables identification of complex mechanisms at surfaces consisting of five chemical elements, overcoming limitations of previous catalysts.

SourceRuhr-University Bochum·JournalAngewandte Chemie International Edition·DateFeb 17, 2021

Russian scientists created a chemical space mapping method and cracked the mystery of Mendeleev number

Researchers from Skoltech have created a universal approach for predicting material properties based on their chemical composition. By assigning a Mendeleev number (MN) to each element, they have shown that this system is more effective than empirical solutions in identifying promising compounds with unique properties.

SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalThe Journal of Physical Chemistry C·DateNov 10, 2020

Plastic can be sustainable

A research project at Friedrich Schiller University Jena aims to develop recyclable plastic materials that can be recycled and reused. The team, led by Prof. Ulrich S. Schubert, plans to study fibre-reinforced materials and nanocomposites with potential applications in aircraft, tennis rackets, and other industries.