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A new quantum dot photoreductant uses 99% less light energy for organic reactions

Chemists at the School of Science of the Hong Kong University of Science and Technology (HKUST) have recently made significant progress in photocatalysis by unveiling a “super” photoreductant, marking a major advancement in organic synthesis.

Quantum dots (QDs) hold great promise as photocatalysts for promoting photoredox chemistry. However, their application in photocatalytic organic transformations has lagged behind that of small molecule photosensitizers due to the limited understanding of their photophysics.

While various studies have explored the generation of hot electrons from QDs as a strategy to enhance photoreduction efficiencies, achieving effective hot-electron generation under has posed a significant challenge.

AI helps discover optimal new material for removing radioactive iodine contamination

Managing radioactive waste is one of the core challenges in the use of nuclear energy. In particular, radioactive iodine poses serious environmental and health risks due to its long half-life (15.7 million years in the case of I-129), high mobility, and toxicity to living organisms.

A Korean research team has successfully used artificial intelligence to discover a new material that can remove iodine for nuclear environmental remediation. The team plans to push forward with commercialization through various industry–academia collaborations, from iodine-adsorbing powders to contaminated water treatment filters.

Professor Ho Jin Ryu’s research team from the Department of Nuclear and Quantum Engineering, in collaboration with Dr. Juhwan Noh of the Digital Chemistry Research Center at the Korea Research Institute of Chemical Technology, developed a technique using AI to discover new materials that effectively remove contaminants. Their research is published in the Journal of Hazardous Materials.

Strong magnetic fields flip angular momentum dynamics in magnetovortical matter

Angular momentum is a fundamental quantity in physics that describes the rotational motion of objects. In quantum physics, it encompasses both the intrinsic spin of particles and their orbital motion around a point. These properties are essential for understanding a wide range of systems, from atoms and molecules to complex materials and high-energy particle interactions.

When a magnetic field is applied to a quantum system, particle spins typically align with or against the field. This well-known effect, known as spin polarization, leads to observable phenomena such as magnetization. Until now, it was widely believed that spin played the dominant role in how particles respond to magnetic fields. However, new research challenges this long-held view.

In this vein, Assistant Professor Kazuya Mameda of Tokyo University of Science, Japan, in collaboration with Professor Kenji Fukushima of School of Science, The University of Tokyo and Dr. Koichi Hattori of Zhejiang University, found that under strong magnetic fields, the of magnetovortical matter becomes more significant than spin effects, leading to reversing the overall direction of angular momentum. The study will be published in Physical Review Letters on July 1, 2025.

New imaging technique captures every twist of polarized light

EPFL scientists have developed a new technique that lets researchers watch, with unprecedented sensitivity, how materials emit polarized light over time.

Light isn’t just bright or dim, colored or plain. Its waves can also twist and turn, in a phenomenon called . Think about the glasses you wear at a 3D movie, which use light polarization to make each eye see a slightly different image, creating the illusion of depth.

Polarization is key for future technologies, from quantum computers to secure communication and holographic displays. Many materials emit light in ways that encode information in its polarization, as if we were using the direction of light waves to send a message. Among these phenomena is a form known as circularly polarized luminescence (CPL), a special type of light emission produced by chiral materials where light waves spiral either left or right as they travel.

Unique method enables simulation of error-correctable quantum computers

Quantum computers still face a major hurdle on their pathway to practical use cases: their limited ability to correct the arising computational errors. To develop truly reliable quantum computers, researchers must be able to simulate quantum computations using conventional computers to verify their correctness—a vital yet extraordinarily difficult task.

Now, in a world-first, researchers from Chalmers University of Technology in Sweden, the University of Milan, the University of Granada, and the University of Tokyo have unveiled a method for simulating specific types of error-corrected quantum computations—a significant leap forward in the quest for robust quantum technologies.

Quantum computers have the potential to solve complex problems that no supercomputer today can handle. In the foreseeable future, ’s computing power is expected to revolutionize fundamental ways of solving problems in medicine, energy, encryption, AI, and logistics.

AI predicts material properties using electron-level information without costly quantum mechanical computations

Researchers in Korea have developed an artificial intelligence (AI) technology that predicts molecular properties by learning electron-level information without requiring costly quantum mechanical calculations. The research was presented at ICLR 2025.

A joint research team led by Senior Researcher Gyoung S. Na from the Korea Research Institute of Chemical Technology (KRICT) and Professor Chanyoung Park from the Korea Advanced Institute of Science and Technology (KAIST) has developed a novel AI method—called DELID (Decomposition-supervised Electron-Level Information Diffusion)—that accurately predicts using electron-level information without performing quantum mechanical computations.

The method achieved state-of-the-art prediction accuracy on real-world datasets consisting of approximately 30,000 experimental molecular data.

DNA as a perfect quantum computer based on the quantum physics principles

I believe that dna will be able to answer just about all our genetic coding questions so much that it will lead to even better breakthroughs in the future and use hardly any energy. I believe also that the master algorithm can eventually be derived from DNA as dna seems already a perfect master algorithm for human beings where human beings are the key to all future progress. I say this as quantum computing is still not stable but we already know that dna computers seem already a masterpiece already especially even organoids of the human brain. Really it becomes really quite simple as even the quantum realm is unstable but dna computers that are quantum would stabilize this currently unstable realm.


Riera Aroche, R., Ortiz García, Y.M., Martínez Arellano, M.A. et al. DNA as a perfect quantum computer based on the quantum physics principles. Sci Rep 14, 11,636 (2024). https://doi.org/10.1038/s41598-024-62539-5

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Robotic eyes mimic human vision for superfast response to extreme lighting

In blinding bright light or pitch-black dark, our eyes can adjust to extreme lighting conditions within a few minutes. The human vision system, including the eyes, neurons, and brain, can also learn and memorize settings to adapt faster the next time we encounter similar lighting challenges.

In an article published in Applied Physics Letters, researchers at Fuzhou University in China created a machine vision sensor that uses quantum dots to adapt to extreme changes in light far faster than the human eye can—in about 40 seconds—by mimicking eyes’ key behaviors. Their results could be a game changer for robotic vision and autonomous vehicle safety.

“Quantum dots are nano-sized semiconductors that efficiently convert light to ,” said author Yun Ye.