CAS QIBEBT: a homogenous cathode material enhances the life cycle of Li batteries dramatically

https://english.news.cn/20240826/bcc0b831623a49e590ff4c21d0c6b68b/c.html

https://www.nature.com/articles/s41560-024-01596-6

A research team from CAS QIBEBT has developed a new homogeneous cathode material, which will enable solid lithium batteries to have higher safety and superior performance, has not yet been named. It achieves over 1,000 times the electronic and ionic conductivity of traditional battery cathode materials. It can smoothly undergo charge and discharge cycles without conductive additives, which simplifies the battery preparation process and also improves the performance of the all-solid-state lithium battery.

Homogeneous cathodes were composed of 100% Li_1.75Ti₂(Ge_0.25P_0.75S_3.8Se_0.2)₃ enable room-temperature all-solid-state lithium batteries to achieve a cycle life of over 20,000 cycles at 2.5 C with a specific capacity retention of 70% and a high energy density of 390 Wh kg⁻¹ at the cell level at 0.1 C. This cathode homogenization strategy contrasts to the conventional cathode heterogeneous design, potentially improving the viability of all-solid-state lithium batteries for commercial applications.

more insights

A humanoid robot training center in Qingdao improves robot efficiency

https://en.people.cn/n3/2026/0324/c90000-20439477.html

At the Qingdao Humanoid Robot Data Training Center in Laoshan District of Qingdao, humanoid robots are trained for jobs such as intelligent industrial manufacturing, smart home, and commercial services. Data collectors here control robots to complete specific tasks like logistics sorting, supermarket restocking, kitchen operations, and component assembly. Through thousands of repetitions and trials, massive amounts of motion data are generated, endowing robots with a smarter “intelligent brain,” and helping humanoid robots enter all walks of life to serve thousands of households.

RamEx: high-throughput microbial ramanome analyses with accurate quality assessment

https://www.cas.cn/syky/202602/t20260226_5102870.shtml

https://doi.org/10.1186/s40168-026-02339-3

A research team at the CAS Qingdao Institute of Bioenergy and Bioprocess Technology has developed RamEx, an integrated analysis framework for Ramanome big data. This platform, tailored to the characteristics of Raman spectroscopy data, establishes a one-stop workflow from data reading and standardized preprocessing to downstream data mining, centered on automated quality control algorithms and efficient parallel computing processes. It also demonstrates a systematic analysis of microbial metabolomical heterogeneity and metabolic pattern differentiation at the single-cell level.

Raman genomics deep analysis can track the dynamic changes in the composition of macromolecules such as lipids, proteins, and nucleic acids in different cells, thus revealing the differentiation and succession patterns of microbial metabolic states at the population scale with single-cell precision. This provides new research ideas and technical pathways for understanding the functional organization and environmental adaptation mechanisms of complex communities.

RamEx removes spectral noise in Raman-based microbial cell sorting

http://english.cas.cn/newsroom/research-news/202602/t20260224_1151116.shtml

https://link.springer.com/article/10.1186/s40168-026-02339-3

Scientists from the CAS Qingdao Institute of Bioenergy and Bioprocess Technology have developed a novel computational tool, RamEx, designed to resolve the computational bottleneck in high-throughput microbial Ramanomics.

RamEx streamlines the full Ramanomic analysis pipeline, from data preprocessing and automated quality control to advanced data mining. An Iterative Convolutional Outlier Detection (ICOD) algorithm tackles spectral noise in an unsupervised manner to dynamically identify and eliminate spectral artifacts, ensuring high-quality input for downstream analysis.

The platform’s performance was validated using diverse datasets, including pathogenic bacteria, probiotics, and yeast fermentation systems. Notably, RamEx successfully captured phenotypic heterogeneity in genetically identical yeast cells by detecting subtle metabolic fluctuations and tracking the dynamic accumulation of intracellular macromolecules, including lipids, proteins, and nucleic acids.

Back to …

青岛 Qingdao
a hub for S&T