Alexander von Humboldt Foundation Grant for Dr. Jie Wei
Dr. Jie Wei strives to further elucidate the nanoscale structure-property relationships at electrocatalytic interfaces for CO2 and CO conversion. © C. Kley / HZB
In April, Dr. Jie Wei started his research work in the Helmholtz Young Investigator Group Nanoscale Operando CO2 Photo-Electrocatalysis at Helmholtz-Zentrum Berlin (HZB) and Fritz Haber Institute (FHI) of the Max Planck Society. Wei received one of the highly competitive Humboldt postdoctoral research fellowships and will pursue his two-year project under the guidance of the academic hosts Dr. Christopher Kley and Prof. Dr. Beatriz Roldan Cuenya.
Jie Wei is a native of China and obtained his PhD in physical chemistry at the University of Science and Technology of China. He spent two years as a postdoc at Tsinghua University (China). His previous works focused on the interface structure and dynamic behavior of catalysts under reaction conditions using (video-rate) electrochemical scanning tunneling microscopy (STM), differential electrochemical mass spectrometry and in situ Raman spectroscopy.
“I applied for a postdoctoral position in this group because of the hosts’ expertise in employing cutting-edge in situ surface-sensitive characterization techniques for advancing fundamental understanding of catalysts under reaction conditions,” says Wei. “Together, HZB and FHI offer a unique range of cutting-edge experimental resources along with a strong theory support for calculation and modeling of solid-liquid interfaces. Having access to such advanced spectroscopic characterization tools, particularly electrochemical atomic force microscopy, is awesome. I strive to further elucidate the nanoscale structure-property relationships at electrocatalytic interfaces for CO2 and CO conversion,” he continues.
From his stay in Berlin, Wei also expects to expand his scientific expertise, moving towards more sundry methodologies and more complex sample systems.
“With Jie’s expertise, we look forward to pushing forward the field of nanoscale electrocatalysis for renewable energy conversion and storage", says Christopher Kley. “A key for our successful research is a very diverse and open environment. I am delighted that Jie will enrich our team with new perspectives and ideas“, Beatriz Roldan Cuenya adds.
HZB and FHI have been collaborating on catalysis research for several years. Together they operate the BMBF funded large-scale Catalysis Laboratory (CatLab).
The Alexander von Humboldt Foundation annually awards various fellowships to outstanding scientists from all over the world in all disciplines. The fellowships are highly prized, and the “Humboltians”-community counts numerous Nobel Prizes.
- Only at BESSY II worldwide: IR nanoscopy at very long THz wavelengthsThe team at the IRIS beamline at BESSY II has created a new experimental option: They achieved infrared nanoscopy with a spatial resolution of around 50 nm at very long THz wavelengths. This was possible thanks to a temporal pattern of light pulses known as the low-alpha operating mode at BESSY II. Worldwide, BESSY II is the only synchrotron light source at which users could perform nanoscopy in a single setup from 25 to 4000 cm-1, a unique opportunity for ultra-broadband characterisation of complex materials at the nanoscale in both the life sciences and materials sciences.
- Ultrafast demagnetisation - Thinner iron, stronger effectThe thinner an iron film, the more easily it can be demagnetised by a laser pulse. Researchers at the University of Duisburg-Essen, working with Helmholtz-Zentrum Berlin and other partners, have discovered why: the key lies in the magnetic order at the material's interfaces. In the long term, these findings could contribute to the development of new technologies for magnetic data storage. The results have been published in the scientific journal Advanced Science.
- Blind spot for the arrangement of atomsArtificial intelligence is increasingly being used to predict the properties of new materials. A research team from Jena and the United States now shows in a study published in the journal Nature Computational Science that when language models are used for this purpose, they reliably identify which types of atoms a material contains. However, they make insufficient use of information about how those atoms are arranged in space. Neither larger models nor additional training data resolve this weakness. For material properties that depend strongly on structure, AI models specifically designed to process spatial relationships are therefore the more reliable choice. (DOI: 10.1038/s43588-026-01045-2)