Synchrotron Radiation News最新文献_第6页

New Opportunities for Earth Science at the Extremely Brilliant Source of the European Synchrotron Radiation Facility 欧洲同步加速器辐射设施的超亮光源为地球科学带来了新机遇

Synchrotron Radiation News Pub Date : 2022-11-02 DOI: 10.1080/08940886.2022.2159711

A. D. Rosa, I. Kupenko, J. Hernández, A. Forestier, M. Muñoz, G. Morard, M. A. Bouhifd, K. Lomachenko, R. Torchio, A. Chumakov, O. Mathon, M. Mezouar

引用次数: 1

SNI2022: German Conference for Research with Synchrotron Radiation, Neutrons, and Ion Beams at Large-Scale Facilities SNI2022：德国同步辐射、中子和离子束大规模研究会议

Synchrotron Radiation News Pub Date : 2022-11-02 DOI: 10.1080/08940886.2022.2161790

J. Lüning

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引用次数: 0

From Outer Space to the Center of the Earth: How NSLS-II Capabilities Enable Geoscience Studies 从外太空到地球中心:NSLS-II能力如何促进地球科学研究

Synchrotron Radiation News Pub Date : 2022-11-02 DOI: 10.1080/08940886.2022.2156752

R. Laasch, Zhenxian Liu, Lu Ma, Sarah Nicholas, P. Northrup, J. Thieme, M. Whitaker

{"title":"From Outer Space to the Center of the Earth: How NSLS-II Capabilities Enable Geoscience Studies","authors":"R. Laasch, Zhenxian Liu, Lu Ma, Sarah Nicholas, P. Northrup, J. Thieme, M. Whitaker","doi":"10.1080/08940886.2022.2156752","DOIUrl":"https://doi.org/10.1080/08940886.2022.2156752","url":null,"abstract":"From extraterrestrial materials to minerals under high pressure deep in Earth’s interior, scientists study the various natural materials and in-terconnected systems of our planet to better understand its origin and evolution, current processes and cycles, and future. This understanding is essential for access to natural resources, preservation of Earth’s critical environment, response to climate change, and protection from natural hazards. To answer important and large-scale questions about our environment, our planet, and our solar system, the keys are often found at the microscale of chemical and physical properties and processes. However, these questions are often so complex that researchers need highly specialized tools to access the intricate details of their samples. As a U.S. Department of Energy (DOE) Office of Science user facil - ity located at DOE’s Brookhaven National Laboratory, the National Synchrotron Light Source II (NSLS-II) provides a wide range of capabilities ideal for studying geological samples. The following highlights describe application of several beamlines at NSLS-II, covering a range of spatial and energy scales, for geological research.","PeriodicalId":39020,"journal":{"name":"Synchrotron Radiation News","volume":"35 1","pages":"2 - 7"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43039785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Synchrotron Radiation and Earth Science 同步辐射与地球科学

Synchrotron Radiation News Pub Date : 2022-11-02 DOI: 10.1080/08940886.2022.2161791

H. Wagner

引用次数: 0

ALS User Meeting and Workshops 2022 ALS User Meeting Highlights ALS用户会议和研讨会2022 ALS用户会议亮点

Synchrotron Radiation News Pub Date : 2022-11-02 DOI: 10.1080/08940886.2022.2159713

Sintu Rongpipi

引用次数: 0

Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering 中子和x射线散射机器学习的挑战和机遇

Synchrotron Radiation News Pub Date : 2022-10-12 DOI: 10.1080/08940886.2022.2112498

Nathan C. Drucker, Tongtong Liu, Zhantao Chen, Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Thanh Nguyen, Yao Wang, Mingda Li

{"title":"Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering","authors":"Nathan C. Drucker, Tongtong Liu, Zhantao Chen, Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Thanh Nguyen, Yao Wang, Mingda Li","doi":"10.1080/08940886.2022.2112498","DOIUrl":"https://doi.org/10.1080/08940886.2022.2112498","url":null,"abstract":"Vol. 35, No. 4, 2022, Synchrotron radiation newS Feature article Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering NathaN C. DruCker,1,2 toNgtoNg Liu,1,3 ZhaNtao CheN,1,4 ryotaro okabe,1,5 abhijatmeDhi ChotrattaNapituk1,6 thaNh NguyeN,1,7 yao WaNg,8 aND miNgDa Li1,7 1Quantum Measurement Group, MIT, Cambridge, Massachusetts, USA 2School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA 3Department of Physics, MIT, Cambridge, Massachusetts, USA 4Department of Mechanical Engineering, MIT, Cambridge, Massachusetts, USA 5Department of Chemistry, MIT, Cambridge, Massachusetts, USA 6Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts, USA 7Department of Nuclear Science and Engineering, MIT, Cambridge, MA, USA 8Department of Physics and Astronomy, Clemson University, Clemson, South Carolina, USA Introduction Machine learning has been highly successful in boosting the research for neutron and X-ray scattering in the past few years [1, 2]. For diffraction, machine learning has shown great promise in phase mapping [3, 4] and crystallographic information determination [5, 6]. In small-angle scattering, machine learning shows the power in reaching super-resolution [7, 8], reconstructing structures for macromolecules [9], and building structure-property relations [10]. As for absorption spectroscopy, machine learning has enabled the rapid inverse search for optimized structures [11, 12] with improved spectral interpretability [13, 14]. Overall, as a data-driven approach, the success of the machinelearning-based scattering analysis depends on a few criteria, including:","PeriodicalId":39020,"journal":{"name":"Synchrotron Radiation News","volume":"35 1","pages":"16 - 20"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42317975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Embedding AI in the Protein Crystallography Workflow 将人工智能嵌入蛋白质晶体学工作流程

Synchrotron Radiation News Pub Date : 2022-10-07 DOI: 10.1080/08940886.2022.2114723

Richard J. Gildea, C. Orr, N. Paterson, D. Hall

{"title":"Embedding AI in the Protein Crystallography Workflow","authors":"Richard J. Gildea, C. Orr, N. Paterson, D. Hall","doi":"10.1080/08940886.2022.2114723","DOIUrl":"https://doi.org/10.1080/08940886.2022.2114723","url":null,"abstract":"Historically, solving the structure of a protein required deep knowledge of crystallography and the ability to produce protein crystals of suitable quality to generate high-quality diffraction data. Over the years, as beamline optics, end-stations, detectors, and data collection strategies have improved, it has become more feasible to extract highquality diffraction data from ever smaller or less perfect protein crystals and from very large arrays of crystals for techniques such as serial synchrotron crystallography and fragment-based drug discovery. At Diamond, these improvements have been coupled with highly integrated automated pipelines for data reduction and structure solution using techniques such as molecular replacement and experimental phasing. This has led to the dichotomy, and benefits, of being able to do increasingly challenging experiments requiring deep crystallographic knowledge with facility staff support at the same time as lowering the barrier to entry where automated structure solution tools of the facility perform this task for those scientists with less experience. This enables users to focus on the science rather than the process. Diamond Light Source, the UK’s national synchrotron, has a suite of instruments dedicated to solving the 3D structure of large biological molecules, including seven macromolecular crystallography (MX) beamlines. Solved 3D structures are deposited into the publicly available Protein Data Bank (PDB) and the depositions are released on a weekly basis. In 2020, following 13 years of operation, Diamond hit the milestone of 10,000 structures deposited in the PDB. Two years on, this number is now more than 12,000. Thanks to decades of work across the world, there is an ocean of information in the PDB that serves as an invaluable reference when solving the structures of new proteins.","PeriodicalId":39020,"journal":{"name":"Synchrotron Radiation News","volume":"35 1","pages":"51 - 54"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48526039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Marking 75 Years of Science with Synchrotron Light 用同步加速器光纪念科学75周年

Synchrotron Radiation News Pub Date : 2022-09-28 DOI: 10.1080/08940886.2022.2114702

Silvana Westbury

引用次数: 0

Advancing AI/ML at the Advanced Photon Source 推进AI/ML在先进光子源

Synchrotron Radiation News Pub Date : 2022-09-22 DOI: 10.1080/08940886.2022.2112500

C. Benmore, Tekin Bicer, M. Chan, Z. Di, Dogˇa Gürsoy, In-hui Hwang, N. Kuklev, Dergan Lin, Zhengchun Liu, I. Lobach, Zhi-wei Qiao, L. Rebuffi, Hemant Sharma, Xianbo Shi, Cheng-wei Sun, Yudong Yao, T. Zhou, A. Sandy, A. Miceli, Yin-e Sun, N. Schwarz, M. Cherukara

引用次数: 2

Annotat3D: A Modern Web Application for Interactive Segmentation of Volumetric Images at Sirius/LNLS Annotat3D:用于天狼星/LNLS的体积图像交互式分割的现代Web应用程序

Synchrotron Radiation News Pub Date : 2022-09-21 DOI: 10.1080/08940886.2022.2112501

Allan Pinto, Gabriel Borin, Bruno Carlos, Matheus Bernardi, Matheus F. Sarmento, Alan Z. Peixinho, T. V. Spina, E. Miqueles

引用次数: 1