毎年行われるWITecペーパーアワード（WITec Paper Award）は、WITec顕微鏡を使用し取得した特徴的な研究データについて、特に優秀と認められる査読付き 論文３件を表彰しています。本年度は、過去最高記録113件のご応募がありました。ほんの一例を挙げますと、半導体研究、電気化学、癌研究、地質学、マイクロプラスチックの研究など、種々の分野で多様なニーズに対しラマンイメージングが有用であることを確認しています。 WITecは、ご応募くださった研究者の皆様に心より感謝申し上げます。本年度のアワードは、電気化学、生物医学、高分子科学の分野において優れたな研究内容と手法が評価された日本、ポーランド、オーストリアの其々の研究者に授与されました。
- GOLD: Ankur Baliyan and Hideto Imai (2019) Machine Learning based Analytical Framework for Automatic Hyperspectral Raman Analysis of Lithium-ion Battery Electrodes. Scientific Reports 9: 18241. doi.org/10.1038/s41598-019-54770-2
- SILVER: Ewelina Wiercigroch, Elzbieta Stepula, Lukasz Mateuszuk, Yuying Zhang, Malgorzata Baranska, Stefan Chlopicki, Sebastian Schlücker and Kamilla Malek (2019) ImmunoSERS Microscopy for the Detection of Smooth Muscle Cells in Atherosclerotic Plaques. Biosensors and Bioelectronics 133: 79-85. doi.org/10.1016/j.bios.2019.02.068
- BRONZE: Ruth Schmidt, Harald Fitzek, Manfred Nachtnebel, Claudia Mayrhofer, Hartmuth Schröttner and Armin Zankel (2019) The Combination of Electron Microscopy, Raman Microscopy and Energy Dispersive X-Ray Spectroscopy for the Investigation of Polymeric Materials. Macromolecular Symposia 384: 1800237. doi.org/10.1002/masy.201800237
For a list of all previous Paper Award winners, please visit www.witec.de/paper-award.
The Paper Award GOLD: Automated quality control of lithium-ion batteries
Lithium-ion batteries (LIBs) provide the power for most electric devices that we use every day, such as cell phones, tablets and laptops. Their development was honored with the Nobel Prize in Chemistry last year. Automated real-time quality control of LIB materials is necessary for industrial research and production. Ankur Baliyan and Hideto Imai from Nissan Arc. (Yokosuka, Japan) win the Gold Paper Award 2020 for their machine learning-based approach to analyzing Raman data of LIBs. Raman images of LIB cathodes can visualize the spatial distribution of the active cathode material (lithium nickel manganese cobalt oxide, abbreviated as LiMO2) and the surrounding carbon matrix. In order to automate and accelerate the process of identifying the spectral signatures in Raman datasets, the authors developed a machine learning-based analytical framework. It starts by automatically pre-processing the Raman data to remove the baseline and cosmic rays. Next, algorithms determine the number of components, extract the corresponding spectral signatures, and identify them. The spectra are finally used to train a neural network, which can then automatically analyze Raman data from the same or a different LIB sample. The authors demonstrated that data analysis by the trained neural network yielded results consistent with results from an experienced user. However, the algorithm found two minor signatures in addition to the main components of carbon and LiMO2 that corresponded to a residual background signal and one of the main components exhibiting increased fluorescence signals. The presented approach requires very little user input and is thus suitable for real-time quality control using Raman data from lithium-ion batteries and other applications.
The Paper Award SILVER: Characterizing atherosclerotic plaques with iSERS microscopy
“Atherosclerosis is one of the major causes of death worldwide. Understanding the mechanism of its formation still remains a great challenge in medicine. Powerful techniques for monitoring the composition and stability of atherosclerotic plaques are thus needed,” says Ewelina Wiercigroch from Jagiellonian University (Krakow, Poland), winner of the Silver Paper Award 2020. Atherosclerotic plaques form at arterial walls and narrow the blood vessels. Monitoring the stability of the plaques is of clinical relevance because their rupture can result in a stroke or heart attack. As smooth muscle cells (SMCs) play a key role in stabilizing the plaques, their presence can serve as a marker for plaque stability. Ewelina Wiercigroch, Elzbieta Stepula, Lukasz Mateuszuk, Yuying Zhang, Malgorzata Baranska, Stefan Chlopicki, Sebastian Schlücker and Kamilla Malek from Jagiellonian University and the University of Duisburg-Essen (Germany) demonstrated the suitability of immuno surface-enhanced Raman scattering (iSERS) microscopy for staining SMCs in atherosclerotic plaques. SERS labels were conjugated either with a primary antibody directed against α-actin of SMCs (direct iSERS) or with an appropriate secondary antibody (indirect iSERS). The iSERS images of mouse artery sections visualized regions containing SMCs and cluster analysis allowed the quantification of the percentage of SMCs located in the plaques. Results from iSERS staining agreed qualitatively and quantitatively with those from immunofluorescence (IF) staining. IF is the current gold standard in visualizing atherosclerotic constituents, but iSERS offers some advantages, such as higher photostability. The study thus establishes iSERS as a promising technique for visualizing and quantifying SMCs in atherosclerotic plaques.
The Paper Award BRONZE: Correlative Raman imaging of polymeric materials
Ruth Schmidt from Graz University of Technology (Graz, Austria) receives the Bronze Paper Award 2020, together with her colleagues Harald Fitzek, Manfred Nachtnebel, Claudia Mayrhofer, Hartmuth Schröttner and Armin Zankel. The group demonstrated the potential of correlative Raman Imaging and Scanning Electron (RISE) microscopy and Energy Dispersive X-Ray Spectroscopy (EDXS) for investigating polymers. Polymeric materials are popular in many applications due to their wide variety of useful properties, such as high elasticity or toughness. For characterizing their properties, the advantages of three imaging techniques were combined. Scanning Electron Microscopy (SEM) acquired high-resolution structural information, while Raman imaging revealed the chemical composition and was complemented by elemental information from EDXS. The publication provides a detailed methodology chapter which describes different sample preparation approaches and imaging modes. For example, it explains strategies for SEM imaging without coating the sample, which would hinder subsequent Raman imaging. Three polymer specimens were investigated with RISE and EDXS, yielding complementary information from the same sample region. Coarse and fine structures of the samples were correlated with chemical properties and the layer structure of packaging materials was visualized. Particulate additives in a polymer matrix were identified and their size distribution was investigated. The authors stressed that combined SEM, Raman imaging and EDXS offers great possibilities for analyzing polymeric materials.
2021年度 WITecペーパーアワード 応募受付中
- Press Release Paper Award 2020 EN (PDF) (686 KB)
- Press Release Paper Award 2020 EN (DOCX) (306 KB)
- Picture Paper Award 2020 Gold (JPG) (2.4 MB)
- Picture Paper Award 2020 Silver Copyright: E. Wiercigroch (JPG) (2.1 MB)
- Picture Paper Award 2020 Bronze Copyright: FELMI-ZFE (JPG) (2.5 MB)