CZI announced its latest AI model, GREmLN, aimed at helping researchers better understand how cells behave by focusing on the key networks that control cell behavior.

Researchers from Seoul National University (Prof. Seung-Kyun Kang), the Korea Institute of Science and Technology, KIST (Dr. Hyojin Lee), Kwangwoon University (Prof. Jeonghyun Kim), and Gyeongsang National University (Prof. Seongchan Kim) have developed a wireless implantable drug delivery system that enables anticancer drugs to penetrate deep into solid tumors—without harming surrounding healthy tissue. The multidisciplinary team, led by experts in materials science, bioelectronics, and pharmaceutical engineering, offers a new strategy to enhance the efficacy of chemotherapy while minimizing side effects.

In a paper published in National Science Review, an international team of scientists provide an overview of the advances in optical two-way time-frequency transfer based on optical fiber, which is a representative of state-of-the-art clock synchronization technology. This review gives a comprehensive discussion of the field from principles, experiments, to future applications, offering a detailed insight into this advanced technology.

A breakthrough study has developed a model that accurately predicts the failure of lithium metal anodes using electrochemical curve data from just the first two cycles. The model offers new insights into failure mechanisms and provides a predictive tool that could speed up the development of more reliable lithium metal batteries, which are critical for high-energy applications.

ChemELLM, a 70-billion-parameter LLM tailored for chemical engineering, outperforms leading LLMs (e.g., Deepseek-R1) on ChemEBench across 101 tasks, trained on ChemEData’s 19 billion pretraining and 1 billion fine-tuning tokens, accelerating lab-to-fab innovation.