It requires 1 billion times less energy than our current systems.

Light-emitting diodes (LEDs), semiconductor-based devices that emit light when an electric current flows through them, are key building blocks of numerous electronic devices. LEDs are used to light up smartphone, computer, and TV displays, as well as light sources for indoor and outdoor environments.

Past studies consistently observed a decline in the performance and efficiency of LED devices based on two-dimensional (2D) materials at high current densities. This loss of efficiency at high current densities has been linked to high levels of interaction between excitons, which cause a process known as exciton-exciton annihilation (EEA).

Essentially, the properties of some 2D materials prompt excitons to strongly interact with each other, causing excitons to “deactivate” one another. This results in a significant waste of energy that could otherwise contribute to the lighting of LEDs.

In a recent study published in Nature Communications, a team of researchers at the Carl R. Woese Institute for Genomic Biology reports a new, robust computational toolset to extract biological relationships from large transcriptomics datasets. These efforts will help scientists better investigate cellular processes.

Living organisms are governed by their genome—an instruction manual written in the language of DNA that dictates how an organism grows, survives, and reproduces. By regulating the abundance of different RNA transcripts, cells control their protein expression level, thereby shaping their functions and responses to the environment.

Transcriptomics is the study of gene expression through cataloging the presence and abundance levels of active RNA transcripts generated from the genome under different conditions. Through the lens of RNA, transcriptomics technologies allow scientists to study the complex interactions that enable life and cause disease, as well as assess the biological effects of therapeutics.

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Cell–cell alignment and a background of stationary cells together shape the emergence of cellular clusters in a primary tumor.

In a cancer patient, tumor cells that circulate throughout the body in clusters pose a greater threat of metastasis than those that circulate individually. Those clusters are thought to come together while the cells are still within the primary tumor, but researchers still don’t understand the formation mechanism. Quirine Braat at Eindhoven University of Technology in the Netherlands and her colleagues have now used computer simulations to identify some of the factors at play [1].

The team used a computational lattice model of cells and tissues (the cellular Potts model) to examine a 2D layer of two types of cells—one motile (able to move) and one nonmotile. The tendency of the motile cells to migrate was represented in the model by an external force applied to each one. For a given cell, this force could align strongly or weakly with the forces acting on its neighboring cells.

A joint research team led by Yuuki Kubo and Shiji Tsuneyuki of the University of Tokyo has developed a new computational method that can efficiently determine the crystal structures of multiphase materials, powders that contain more than one type of crystal structures. The method can predict the structure directly from powder X-ray diffraction patterns, the patterns of X-rays passing through crystals roughly the same size as instant coffee particles.

Unlike conventional methods, this approach does not require the use of “lattice constants” and can be applied to existing experimental data that could not be analyzed until now. Thus, the new method is a crucial asset for discovering new material phases and developing new materials. The findings are published in The Journal of Chemical Physics.

Many materials can have several crystal structures, “phases,” even in the same solid state. Determining the underlying crystal structures of materials is essential for understanding their properties and formulating strategies to develop new materials. However, conventional methods make calculations using the “lattice constant,” a property of the crystal being investigated.

Polarization photodetectors (pol-PDs) have widespread applications in geological remote sensing, machine vision, and biological medicine. However, commercial pol-PDs usually require bulky and complicated optical components and are difficult to miniaturize and integrate.

Chinese researchers have made important progress in this area by developing an on-chip integrated polarization photodetector.

This study, published in Science Advances on Dec. 4, was conducted by Prof. Li Mingzhu’s group from the Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences.

Transistors based on two-dimensional (2D) semiconductors, such as molybdenum disulfide (MoS₂) and tungsten diselenide (WSe₂), could outperform conventional silicon-based transistors, while also being easier to reduce in size. To perform well, these transistors need to be based on high-quality dielectric materials, which can be difficult to prepare.

Researchers at Nanyang Technological University, Nanjing University of Aeronautics and Astronautics recently introduced a new promising strategy to prepare the dielectric materials for these transistors. Their approach, outlined in a paper published in Nature Electronics, was successfully used to deposit an ultrathin and uniform native oxide of gallium Ga₂O₃ on the surface of MoS₂.

“Traditional methods of preparing dielectric layer, such as atomic layer deposition (ALD), encounter quality problems because of the high-quality surface of 2D semiconductors without sufficient nucleation points, especially at thin thicknesses down to a few nanometers,” Kongyang Yi, first author of the paper, told Tech Xplore.

Researchers have developed an innovative optical technology capable of enhancing data transmission by utilizing spatial-frequency patching metasurfaces.

This approach allows light beams to carry significantly more data across multiple independent channels, overcoming traditional optical beam limitations. Its applications extend to secure communication, encryption, and advanced optical systems.

Revolutionary optical technology for data transmission.

Quantum chaos, previously theoretical, has been observed experimentally, validating a 40-year-old theory about electrons forming patterns in confined spaces.

Using advanced imaging techniques on graphene, researchers confirmed “quantum scars,” where electrons follow unique closed orbits. These findings could revolutionize electronics by enabling efficient, low-power transistors and paving the way for novel quantum control methods. This discovery offers insights into chaotic quantum systems, bridging a gap between classical and quantum physics.

Patterns in chaos revealed in quantum space.