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Molecular Foundry

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The Molecular Foundry is a nanoscience user facility located at the Lawrence Berkeley National Laboratory in Berkeley, California , and is one of five Nanoscale Science Research Centers sponsored by the United States Department of Energy .

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20-516: The Molecular Foundry was founded in 2003. The building was completed on March 24, 2006. The current director, Kristin Persson , was appointed in 2020, following permanent directors Jeff Neaton (2013–2019), Omar Yaghi (2012–2013) and Carolyn Bertozzi (2006–2010). Users of the Molecular Foundry are provided with free access to instruments, techniques and collaborators for nanoscience research that

40-634: A Master of Science in engineering physics from Lund Institute of Technology in Sweden and completed a Ph.D. in theoretical physics from Royal Institute of Technology (KTH) in Sweden in 2001, under the supervision of Göran Grimvall . After her Ph.D., she joined the Massachusetts Institute of Technology as a postdoctoral associate from 2001 to 2002. In 2002 she resigned her postdoctoral position to care full-time for her two daughters, born 2000 and 2002. She

60-620: Is addressed by the Materials Research Society . For example, materials informatics was the theme of the December 2006 issue of the MRS Bulletin . The issue was guest-edited by John Rodgers of Innovative Materials, Inc., and David Cebon of Cambridge University , who described the "high payoff for developing methodologies that will accelerate the insertion of materials, thereby saving millions of investment dollars." The editors focused on

80-593: Is at the convergence of these concepts, but also transcends them and has the potential to achieve greater insights and deeper understanding by applying lessons learned from data gathered on one type of material to others. By gathering appropriate meta data, the value of each individual data point can be greatly expanded. Databases are essential for any informatics research and applications. In material informatics many databases exist containing both empirical data obtained experimentally, and theoretical data obtained computationally. Big data that can be used for machine learning

100-486: Is in the public domain and intended for open publication. Proposals for user projects are aimed to promote interdisciplinary collaboration in the areas of materials science , physics , electrical engineering , environmental engineering , biology and chemistry . The foundry includes these seven facilities: The Molecular Foundry has a user program that gives access to the center's staff and equipment to external researchers who intend to publish their results. The program

120-603: Is open to scientists from academia, industry, and research institutes. The application process for the user program involves submitting a peer-reviewed proposal. 37°52′30″N 122°14′33″W  /  37.8749°N 122.2425°W  / 37.8749; -122.2425 Kristin Persson Kristin Aslaug Persson is a Swedish/Icelandic American physicist and chemist. She was born in Lund, Sweden, in 1971, to Eva Haettner-Aurelius and Einar Benedikt Olafsson. She

140-602: Is particularly difficult to obtain for experimental data due to the lack of a standard for reporting data and the variability in the experimental environment. This lack of big data has led to growing effort in developing machine learning techniques that utilize data extremely data sets. On the other hand, large uniform database of theoretical density functional theory (DFT) calculations exists. These databases have proven their utility in high-throughput material screening and discovery. Some common DFT databases and high throughput tools are listed below: The concept of materials informatics

160-563: Is the Daniel M. Tellep Distinguished Professor of Materials Science and Engineering at University of California, Berkeley and a faculty senior staff scientist at Lawrence Berkeley National Laboratory . Between 2020-2024, she served as the director of the Molecular Foundry , a national user facility managed by the US Department of Energy at Lawrence Berkeley National Laboratory . Persson

180-538: Is the director and founder of the Materials Project , a multi-national effort to compute the properties of all inorganic materials. Her research group focuses on the data-driven computational design and prediction of new materials for clean energy production and storage applications. In 2024, Persson was elected a member of the Royal Swedish Academy of Sciences , in the class of Chemistry. Persson holds

200-515: The Materials Project,⁣ a collaborative and international initiative that calculates the properties of all inorganic materials. This project provides researchers with free access to the data and related analysis algorithms. The main objective of the Materials Project is to significantly reduce the time required to develop new materials by focusing experimental efforts on compounds that show the most promise based on computational analysis. Within

220-472: The Persson Group, researchers apply their expertise in materials informatics and the high-throughput infrastructure of the Materials Project to design innovative materials for various clean energy applications. These materials include photocatalysts, multi-valent battery electrode materials, piezoelectrics, and electrolytes for advanced energy storage solutions. Some of the group's past research has explored

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240-691: The area of data-driven materials design have been honored by the following awards and recognitions: She has also given named lectures such as the Cooper Lecture, West Virginia University , the Distinguished Su Lectureship, University of Rochester and the Dresselhaus Memorial Lecture, IWAM 2023. Materials informatics Materials informatics is a field of study that applies the principles of informatics and data science to materials science and engineering to improve

260-428: The entire materials research enterprise." This remaining tension between traditional materials development methodologies and the use of more computationally, machine learning, and analytics approaches will likely exist for some time as the materials industry overcomes some of the cultural barriers necessary to fully embrace such new ways of thinking. The overarching goals of bioinformatics and systems biology may provide

280-446: The future of informatics in the materials development and scaling process, many challenges remain. Hill, et al., write that "Today, the materials community faces serious challenges to bringing about this data-accelerated research paradigm, including diversity of research areas within materials, lack of data standards, and missing incentives for sharing, among others. Nonetheless, the landscape is rapidly changing in ways that should benefit

300-466: The limited definition of materials informatics as primarily focused on computational methods to process and interpret data. They stated that "specialized informatics tools for data capture, management, analysis, and dissemination" and "advances in computing power, coupled with computational modeling and simulation and materials properties databases" will enable such accelerated insertion of materials. A broader definition of materials informatics goes beyond

320-482: The properties of lithium-graphene, phase transformations in high-voltage nickel-manganese spinel, intercalation mechanisms in lithium excess materials, novel oxide photocatalysts, and the correlation between solvation structure and electrolyte performance in multi-valent electrolytes. The Persson group collaborates with other Materials Project contributors such as Gerbrand Ceder's group, Shyue Ping Ong's group, and Anubhav Jain's group . Persson's accomplishments in

340-442: The time and risk required to develop, produce, and deploy new materials, which generally takes longer than 20 years. This field of endeavor is not limited to some traditional understandings of the relationship between materials and information. Some more narrow interpretations include combinatorial chemistry , process modeling , materials databases, materials data management , and product life cycle management . Materials informatics

360-419: The understanding, use, selection , development, and discovery of materials. The term "materials informatics" is frequently used interchangeably with "data science", "machine learning", and "artificial intelligence" by the community. This is an emerging field, with a goal to achieve high-speed and robust acquisition, management, analysis, and dissemination of diverse materials data with the goal of greatly reducing

380-497: The use of computational methods to carry out the same experimentation, viewing materials informatics as a framework in which a measurement or computation is one step in an information-based learning process that uses the power of a collective to achieve greater efficiency in exploration. When properly organized, this framework crosses materials boundaries to uncover fundamental knowledge of the basis of physical, mechanical, and engineering properties. While there are many who believe in

400-661: Was rehired at MIT in 2004 and became a Research Associate in 2006. In 2008, Persson joined Lawrence Berkeley National Laboratory as a staff scientist, and in 2015 she became a professor in the Department of Materials Science and Engineering at the University of California, Berkeley . The Persson Group is a research team that investigates materials' physics and chemistry using advanced computational methods and high-performance computing technology. Their work primarily supports clean energy production and storage applications. Persson leads

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