Wiley launches its first Spectral Analysis API portfolio, giving labs a faster path from unknown substance to validated answer
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This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 3-Nov-2026 10:16 ET (3-Nov-2026 15:16 GMT/UTC)
To what extent does the allocation of aid for combating disease correspond to disease burden? LMU researchers have developed a machine learning pipeline that helps uncover relative discrepancies in aid distribution.
LMU researchers have developed a molecular building block that can be used to combine proteins and artificial molecules in a targeted way to form complex nanostructures.
Windows contribute significantly to energy inefficiency across global infrastructure. Overcoming complex trade-offs in multispectral optical responses, scientists in China have developed a physics-guided neural network to design energy-efficient thermochromic smart windows for directional privacy protection. These inverse-designed windows achieve ultrahigh simultaneous modulation of near-infrared transmittance and longwave infrared emissivity. Applied to electric vehicles and building envelopes, these customized smart windows demonstrate superior, climate-adaptive all-weather thermal management.
When a pattern drawn only in black and white is rotated, people sometimes perceive colors that are not actually present. This phenomenon is known as “subjective color” and has been studied for approximately 200 years as one of the remarkable mysteries of vision. Among such phenomena, Benham’s top is a well-known example in which colors are perceived simply by spinning a black-and-white disk. A research group led by Associate Professor Eiji Watanabe of NIBB used an artificial neural network trained through predictive learning to investigate the mechanism underlying this subjective color phenomenon. The research group presented a black-and-white Benham’s top to an AI model that had been trained to predict “what kind of image will come next” after viewing natural videos. Although the input images contained no color information at all, faint colors appeared in the images predicted by the AI. Furthermore, the artificially generated colors were found to change depending on the colors of moving objects contained in the videos used to train the AI. Analyses using natural videos, 3D computer graphics, and simple two-dimensional videos of moving red, green, and blue squares suggested that learning the association between motion and color may be one factor that enables colors to emerge from black-and-white stimuli. This study suggests that subjective color may not be a phenomenon completed solely within the retina, but may also be related to the brain’s function of predicting future visual input based on past experience. By using AI, the study provides a new clue to the classical mystery of why colors are perceived from a black-and-white spinning top. These findings were published in Scientific Reports.
Researchers developed asymmetric [3+2+1] coordinated iridium(III) complexes featuring strong electron-withdrawing groups for deep-blue phosphorescent OLEDs. The optimized device achieved a record external quantum efficiency of 29.0% with CIE coordinates of (0.147, 0.089), meeting NTSC standards. A hyper-OLED demonstrated an operational lifetime exceeding 2000 hours, and the emitters were successfully integrated into microdisplay technology.