High-performance and low-cost oxygen reduction reaction (ORR) electrocatalysts are essential for the next generation of energy conversion devices, such as zinc-air batteries and fuel cells. While platinum (Pt)-based materials remain the commercial standard, their widespread adoption is hindered by high costs and poor long-term durability.

A firefly-inspired AI framework makes atomic structure prediction more robust by combining multimodal search with an uncertainty-aware machine learning technique. The method improves efficiency for copper surface oxides and recovers competing gold nanocluster structures in a single run.

- Prof. Sangwon Seo’s team successfully achieved enantioselective synthesis, selectively producing only the desired mirror-image molecule using nickel—a common metal—instead of expensive noble metals - Expected to make a breakthrough contribution to drug development that fundamentally blocks side effects and to the high-value precision chemical industry - Published in the top-tier international chemistry journal Angewandte Chemie – International Edition

Dragonflies have evolved special light-sensing proteins that let them see deeper red light than most animals. Researchers have now discovered that the mechanism of red vision is shared with humans and this ability comes from small molecular changes that could inspire new biomedical technologies.

Nagoya University researchers demonstrated that native soil bacteria, when treated with decoy molecules, can degrade non-native compounds, including persistent pollutants such as dioxins, without genetic modification.

The absence of a signal could itself be a signal. This is the idea behind a new study published in the Journal of Cosmology and Astroparticle Physics (JCAP), which aims to redefine how we search for dark matter, showing that it may not be necessary to find the same “clues” everywhere in order to interpret it. In particular, the study suggests that even if we observe a certain type of signal at the center of our galaxy — an excess of gamma radiation that could result from the annihilation of dark matter particles — failing to detect the same signal in other systems, such as dwarf galaxies, is not enough to rule out this explanation. Dark matter, in fact, may not consist of a single particle, but of multiple slightly different components, whose behavior varies depending on the cosmic environment.

The practical of hard carbon (HC) anodes in sodium-ion batteries is primarily limited by their unsatisfactory initial coulombic efficiency (ICE), cycling stability and rate performance, which are closely related to their interphase chemistry and microstructure. Herein, a unique manipulating interphase chemistry strategy by endogenous N/S doping is proposed to simultaneously achieve the both issues. Specifically, a series of reducing sugars and amino acid have been proven to trigger the Maillard reaction, thereby enabling endogenous N/S doping and microstructural design for HC anodes. Endogenous doping facilitates the formation of an inorganic-enriched solid–electrolyte interface (SEI) layer on cycled HC, which can effectively accelerate ion transport kinetics and reduce side effects for enhanced rate, ICE, cycling performance and reversible capacity. Meanwhile, the increase in the number of closed pores boosts both the platform capacity and cycling stability of HC. Consequently, the features HC anodes demonstrate a splendid reversible capacity (363 mAh g⁻¹ at 0.05 A g⁻¹), superior cycling performance (over 2500 cycles with 79% retention at 5.0 A g⁻¹) and adequate ICE (89%). The assembled full cell with Na₃V₂(PO₄)₃ cathode exhibits splendid cycling stability over 700 cycles with capacity retention of 89.2% at 1 C. Surprisingly, the pouch cell with high cathode mass loading of 20.7 mg cm⁻¹ maintains 98.1% capacity retention after 175 cycles at 1 C. This strategy provides new ideas and insights for the design and screening of high-performance HC anodes.

Under the foundation of research cooperation established through the Ministry of Science and ICT's InnoCORE (InnoCORE) project, KAIST InnoCORE researchers have derived meaningful research results. Following a visit by Professor David Baker (University of Washington, USA), the 2024 Nobel Laureate in Chemistry, KAIST has revealed research findings on designing proteins that accurately recognize desired compounds using AI through joint research.