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  • richardmitnick 3:22 pm on October 18, 2022 Permalink | Reply
    Tags: "Machine learning predicts heat capacities of Metal-Organic Framework materials", , , MOFs-Metal-organic frameworks,   

    From The Swiss Federal Institute of Technology in Lausanne [EPFL-École Polytechnique Fédérale de Lausanne] (CH): “Machine learning predicts heat capacities of Metal-Organic Framework materials” 

    From The Swiss Federal Institute of Technology in Lausanne [EPFL-École Polytechnique Fédérale de Lausanne] (CH)

    10.18.22
    Nik Papageorgiou

    1
    Chemical engineers at EPFL have developed a machine-learning model that can accurately predict the heat capacity of the versatile metal-organic framework materials. The work shows that the overall energy costs of carbon-capture processes could be much lower than expected.

    Metal-organic frameworks (MOFs) are a class of materials that contain nano-sized pores. These pores give MOFs record-breaking internal surface areas, which make them extremely versatile for a number of applications: separating petrochemicals and gases, mimicking DNA, producing hydrogen, and removing heavy metals, fluoride anions, and even gold from water are just a few examples.

    MOFs are the focus of Professor Berend Smit’s research at EPFL School of Basic Sciences, where his group employs machine learning to make breakthroughs in the discovery, design, and even categorization of the ever-increasing MOFs that currently flood chemical databases.

    In a new study [Nature Materials (below)], Smit and his colleagues have developed a machine-learning model that predicts the heat capacity of MOFs. “This is about very classical thermodynamics,” says Smit. “How much energy is needed to heat up a material by one degree? Until now, all engineering calculations have assumed that all MOFs have the same heat capacity, for the simple reason that there is hardly any data available.” Seyed Mohamad Moosavi, a postdoc at Smit’s group, adds: “If there is no data, how can one make a machine-learning model? That looks impossible!”

    The answer is the most innovative aspect of the work: a machine-learning model that predicts how the local chemical environment changes the vibrations of each atom in a MOF molecule. “These vibrations can be related to the heat capacity,” says Smit. “Before, a very expensive quantum calculation would give us a single heat capacity for a single material, but now we get up to 200 data points on these vibrations. So, by doing 200 expensive calculations, we had 40,000 data points to train the model on how these vibrations depend on their chemical environment.”

    The researchers then tested their model against experimental data as a real-life check. “The results were surprisingly poor,” says Smit, “until we realized that those experiments had been done with MOFs that had solvent in their pores. So, we re-synthesized some MOFs and carefully removed the synthesis solvent –measured their heat capacity – and the results were in very good agreement with our model’s predictions!”

    “Our research showcases how Artificial Intelligence (AI) can accelerate solving multi-scale problems,” says Moosavi. AI empowers us to think about our problems in a new way and even sometimes tackle them.”

    To demonstrate the real-world impact of the work, engineers at Heriot-Watt University simulated the MOFs performance in a carbon capture plant. “We used quantum molecular simulations, machine learning, and chemical engineering in process simulations,” says Smit. “The results showed that with correct heat capacity values of MOFs the overall energy cost of the carbon capture process can be much lower than we originally assumed. Our work is a true multi-scale effort, with a huge impact on the techno-economic viability of currently considered solutions to tackle climate change.”

    Science paper:
    Nature Materials

    See the full article here .

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    EPFL bloc

    EPFL campus

    The Swiss Federal Institute of Technology in Lausanne [EPFL-École Polytechnique Fédérale de Lausanne] (CH) is a research institute and university in Lausanne, Switzerland, that specializes in natural sciences and engineering. It is one of the two Swiss Federal Institutes of Technology, and it has three main missions: education, research and technology transfer.

    The QS World University Rankings ranks EPFL(CH) 14th in the world across all fields in their 2020/2021 ranking, whereas Times Higher Education World University Rankings ranks EPFL(CH) as the world’s 19th best school for Engineering and Technology in 2020.

    EPFL(CH) is located in the French-speaking part of Switzerland; the sister institution in the German-speaking part of Switzerland is The Swiss Federal Institute of Technology ETH Zürich [Eidgenössische Technische Hochschule Zürich] (CH). Associated with several specialized research institutes, the two universities form The Domain of the Swiss Federal Institutes of Technology (ETH Domain) [ETH-Bereich; Domaine des Écoles Polytechniques Fédérales] (CH) which is directly dependent on the Federal Department of Economic Affairs, Education and Research. In connection with research and teaching activities, EPFL(CH) operates a nuclear reactor CROCUS; a Tokamak Fusion reactor; a Blue Gene/Q Supercomputer; and P3 bio-hazard facilities.

    ETH Zürich, EPFL (Swiss Federal Institute of Technology in Lausanne) [École Polytechnique Fédérale de Lausanne](CH), and four associated research institutes form The Domain of the Swiss Federal Institutes of Technology (ETH Domain) [ETH-Bereich; Domaine des Écoles polytechniques fédérales] (CH) with the aim of collaborating on scientific projects.

    The roots of modern-day EPFL(CH) can be traced back to the foundation of a private school under the name École Spéciale de Lausanne in 1853 at the initiative of Lois Rivier, a graduate of the École Centrale Paris (FR) and John Gay the then professor and rector of the Académie de Lausanne. At its inception it had only 11 students and the offices were located at Rue du Valentin in Lausanne. In 1869, it became the technical department of the public Académie de Lausanne. When the Académie was reorganized and acquired the status of a university in 1890, the technical faculty changed its name to École d’Ingénieurs de l’Université de Lausanne. In 1946, it was renamed the École polytechnique de l’Université de Lausanne (EPUL). In 1969, the EPUL was separated from the rest of the University of Lausanne and became a federal institute under its current name. EPFL(CH), like ETH Zürich (CH), is thus directly controlled by the Swiss federal government. In contrast, all other universities in Switzerland are controlled by their respective cantonal governments. Following the nomination of Patrick Aebischer as president in 2000, EPFL(CH) has started to develop into the field of life sciences. It absorbed the Swiss Institute for Experimental Cancer Research (ISREC) in 2008.

    In 1946, there were 360 students. In 1969, EPFL(CH) had 1,400 students and 55 professors. In the past two decades the university has grown rapidly and as of 2012 roughly 14,000 people study or work on campus, about 9,300 of these being Bachelor, Master or PhD students. The environment at modern day EPFL(CH) is highly international with the school attracting students and researchers from all over the world. More than 125 countries are represented on the campus and the university has two official languages, French and English.

    Organization

    EPFL is organized into eight schools, themselves formed of institutes that group research units (laboratories or chairs) around common themes:

    School of Basic Sciences
    Institute of Mathematics
    Institute of Chemical Sciences and Engineering
    Institute of Physics
    European Centre of Atomic and Molecular Computations
    Bernoulli Center
    Biomedical Imaging Research Center
    Interdisciplinary Center for Electron Microscopy
    MPG-EPFL Centre for Molecular Nanosciences and Technology
    Swiss Plasma Center
    Laboratory of Astrophysics

    School of Engineering

    Institute of Electrical Engineering
    Institute of Mechanical Engineering
    Institute of Materials
    Institute of Microengineering
    Institute of Bioengineering

    School of Architecture, Civil and Environmental Engineering

    Institute of Architecture
    Civil Engineering Institute
    Institute of Urban and Regional Sciences
    Environmental Engineering Institute

    School of Computer and Communication Sciences

    Algorithms & Theoretical Computer Science
    Artificial Intelligence & Machine Learning
    Computational Biology
    Computer Architecture & Integrated Systems
    Data Management & Information Retrieval
    Graphics & Vision
    Human-Computer Interaction
    Information & Communication Theory
    Networking
    Programming Languages & Formal Methods
    Security & Cryptography
    Signal & Image Processing
    Systems

    School of Life Sciences

    Bachelor-Master Teaching Section in Life Sciences and Technologies
    Brain Mind Institute
    Institute of Bioengineering
    Swiss Institute for Experimental Cancer Research
    Global Health Institute
    Ten Technology Platforms & Core Facilities (PTECH)
    Center for Phenogenomics
    NCCR Synaptic Bases of Mental Diseases

    College of Management of Technology

    Swiss Finance Institute at EPFL
    Section of Management of Technology and Entrepreneurship
    Institute of Technology and Public Policy
    Institute of Management of Technology and Entrepreneurship
    Section of Financial Engineering

    College of Humanities

    Human and social sciences teaching program

    EPFL Middle East

    Section of Energy Management and Sustainability

    In addition to the eight schools there are seven closely related institutions

    Swiss Cancer Centre
    Center for Biomedical Imaging (CIBM)
    Centre for Advanced Modelling Science (CADMOS)
    École Cantonale d’art de Lausanne (ECAL)
    Campus Biotech
    Wyss Center for Bio- and Neuro-engineering
    Swiss National Supercomputing Centre

     
  • richardmitnick 6:13 pm on March 11, 2022 Permalink | Reply
    Tags: "Computational modeling guides development of new materials", , , , , Made of metal atoms linked by organic molecules, , MOF's consist of metal atoms joined by organic molecules called linkers to create a rigid cage-like structure., MOF’s can be configured in hundreds of thousands of different ways., MOFs-Metal-organic frameworks, , The materials have many pores which makes them useful for catalyzing reactions involving gases but can also make them less structurally stable., The MIT team is now using the model to try to identify MOFs that could be used to catalyze the conversion of methane gas to methanol which could be used as fuel., This work will allow researchers to test the promise of specific materials before they go through the trouble of synthesizing them.   

    From The Massachusetts Institute of Technology (US): “Computational modeling guides development of new materials” 

    MIT News

    From The Massachusetts Institute of Technology (US)

    March 11, 2022

    1
    MIT computational chemists developed a model that can analyze the features of a metal-organic framework structure and predict if it will be stable enough to be useful. Image: Courtesy of the researchers.

    Metal-organic frameworks, a class of materials with porous molecular structures, have a variety of possible applications, such as capturing harmful gases and catalyzing chemical reactions. Made of metal atoms linked by organic molecules, they can be configured in hundreds of thousands of different ways.

    To help researchers sift through all of the possible metal-organic framework (MOF) structures and help identify the ones that would be most practical for a particular application, a team of MIT computational chemists has developed a model that can analyze the features of a MOF structure and predict if it will be stable enough to be useful.

    The researchers hope that these computational predictions will help cut the development time of new MOFs.

    “This will allow researchers to test the promise of specific materials before they go through the trouble of synthesizing them,” says Heather Kulik, an associate professor of chemical engineering at MIT.

    The MIT team is now working to develop MOFs that could be used to capture methane gas and convert it to useful compounds such as fuels.

    The researchers described their new model in two papers, one in the Journal of the American Chemical Society and one in Scientific Data. Graduate students Aditya Nandy and Gianmarco Terrones are the lead authors of the Scientific Data paper, and Nandy is also the lead author of the JACS paper. Kulik is the senior author of both papers.

    Modeling structure

    MOF’s consist of metal atoms joined by organic molecules called linkers to create a rigid cage-like structure. The materials have many pores which makes them useful for catalyzing reactions involving gases but can also make them less structurally stable.

    “The limitation in seeing MOFs realized at industrial scale is that although we can control their properties by controlling where each atom is in the structure, they’re not necessarily that stable, as far as materials go,” Kulik says. “They’re very porous and they can degrade under realistic conditions that we need for catalysis.”

    Scientists have been working on designing MOFs for more than 20 years, and thousands of possible structures have been published. A centralized repository contains about 10,000 of these structures but is not linked to any of the published findings on the properties of those structures.

    Kulik, who specializes in using computational modeling to discover structure-property relationships of materials, wanted to take a more systematic approach to analyzing and classifying the properties of MOFs.

    “When people make these now, it’s mostly trial and error. The MOF dataset is really promising because there are so many people excited about MOFs, so there’s so much to learn from what everyone’s been working on, but at the same time, it’s very noisy and it’s not systematic the way it’s reported,” she says.

    Kulik and her colleagues set out to analyze published reports of MOF structures and properties using a natural-language-processing algorithm. Using this algorithm, they scoured nearly 4,000 published papers, extracting information on the temperature at which a given MOF would break down. They also pulled out data on whether particular MOFs can withstand the conditions needed to remove solvents used to synthesize them and make sure they become porous.

    Once the researchers had this information, they used it to train two neural networks to predict MOFs’ thermal stability and stability during solvent removal, based on the molecules’ structure.

    “Before you start working with a material and thinking about scaling it up for different applications, you want to know will it hold up, or is it going to degrade in the conditions I would want to use it in?” Kulik says. “Our goal was to get better at predicting what makes a stable MOF.”

    Better stability

    Using the model, the researchers were able to identify certain features that influence stability. In general, simpler linkers with fewer chemical groups attached to them are more stable. Pore size is also important: Before the researchers did their analysis, it had been thought that MOFs with larger pores might be too unstable. However, the MIT team found that large-pore MOFs can be stable if other aspects of their structure counteract the large pore size.

    “Since MOFs have so many things that can vary at the same time, such as the metal, the linkers, the connectivity, and the pore size, it is difficult to nail down what governs stability across different families of MOFs,” Nandy says. “Our models enable researchers to make predictions on existing or new materials, many of which have yet to be made.”

    The researchers have made their data and models available online. Scientists interested in using the models can get recommendations for strategies to make an existing MOF more stable, and they can also add their own data and feedback on the predictions of the models.

    The MIT team is now using the model to try to identify MOFs that could be used to catalyze the conversion of methane gas to methanol which could be used as fuel. Kulik also plans to use the model to create a new dataset of hypothetical MOFs that haven’t been built before but are predicted to have high stability. Researchers could then screen this dataset for a variety of properties.

    “People are interested in MOFs for things like quantum sensing and quantum computing, all sorts of different applications where you need metals distributed in this atomically precise way,” Kulik says.

    The research was funded by DARPA, the U.S. Office of Naval Research, the U.S. Department of Energy, a National Science Foundation Graduate Research Fellowship, a Career Award at the Scientific Interface from the Burroughs Wellcome Fund, and an AAAS Marion Milligan Mason Award.

    See the full article here .


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    MIT Seal

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

    The Massachusetts Institute of Technology (US) is a private land-grant research university in Cambridge, Massachusetts. The institute has an urban campus that extends more than a mile (1.6 km) alongside the Charles River. The institute also encompasses a number of major off-campus facilities such as the MIT Lincoln Laboratory (US), the MIT Bates Research and Engineering Center (US), and the Haystack Observatory (US), as well as affiliated laboratories such as the Broad Institute of MIT and Harvard(US) and Whitehead Institute (US).

    Massachusettes Institute of Technology-Haystack Observatory(US) Westford, Massachusetts, USA, Altitude 131 m (430 ft).

    Founded in 1861 in response to the increasing industrialization of the United States, Massachusetts Institute of Technology (US) adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. It has since played a key role in the development of many aspects of modern science, engineering, mathematics, and technology, and is widely known for its innovation and academic strength. It is frequently regarded as one of the most prestigious universities in the world.

    As of December 2020, 97 Nobel laureates, 26 Turing Award winners, and 8 Fields Medalists have been affiliated with MIT as alumni, faculty members, or researchers. In addition, 58 National Medal of Science recipients, 29 National Medals of Technology and Innovation recipients, 50 MacArthur Fellows, 80 Marshall Scholars, 3 Mitchell Scholars, 22 Schwarzman Scholars, 41 astronauts, and 16 Chief Scientists of the U.S. Air Force have been affiliated with The Massachusetts Institute of Technology (US) . The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. Massachusetts Institute of Technology (US) is a member of the Association of American Universities (AAU).

    Foundation and vision

    In 1859, a proposal was submitted to the Massachusetts General Court to use newly filled lands in Back Bay, Boston for a “Conservatory of Art and Science”, but the proposal failed. A charter for the incorporation of the Massachusetts Institute of Technology, proposed by William Barton Rogers, was signed by John Albion Andrew, the governor of Massachusetts, on April 10, 1861.

    Rogers, a professor from the University of Virginia (US), wanted to establish an institution to address rapid scientific and technological advances. He did not wish to found a professional school, but a combination with elements of both professional and liberal education, proposing that:

    “The true and only practicable object of a polytechnic school is, as I conceive, the teaching, not of the minute details and manipulations of the arts, which can be done only in the workshop, but the inculcation of those scientific principles which form the basis and explanation of them, and along with this, a full and methodical review of all their leading processes and operations in connection with physical laws.”

    The Rogers Plan reflected the German research university model, emphasizing an independent faculty engaged in research, as well as instruction oriented around seminars and laboratories.

    Early developments

    Two days after Massachusetts Institute of Technology (US) was chartered, the first battle of the Civil War broke out. After a long delay through the war years, MIT’s first classes were held in the Mercantile Building in Boston in 1865. The new institute was founded as part of the Morrill Land-Grant Colleges Act to fund institutions “to promote the liberal and practical education of the industrial classes” and was a land-grant school. In 1863 under the same act, the Commonwealth of Massachusetts founded the Massachusetts Agricultural College, which developed as the University of Massachusetts Amherst (US)). In 1866, the proceeds from land sales went toward new buildings in the Back Bay.

    Massachusetts Institute of Technology (US) was informally called “Boston Tech”. The institute adopted the European polytechnic university model and emphasized laboratory instruction from an early date. Despite chronic financial problems, the institute saw growth in the last two decades of the 19th century under President Francis Amasa Walker. Programs in electrical, chemical, marine, and sanitary engineering were introduced, new buildings were built, and the size of the student body increased to more than one thousand.

    The curriculum drifted to a vocational emphasis, with less focus on theoretical science. The fledgling school still suffered from chronic financial shortages which diverted the attention of the MIT leadership. During these “Boston Tech” years, Massachusetts Institute of Technology (US) faculty and alumni rebuffed Harvard University (US) president (and former MIT faculty) Charles W. Eliot’s repeated attempts to merge MIT with Harvard College’s Lawrence Scientific School. There would be at least six attempts to absorb MIT into Harvard. In its cramped Back Bay location, MIT could not afford to expand its overcrowded facilities, driving a desperate search for a new campus and funding. Eventually, the MIT Corporation approved a formal agreement to merge with Harvard, over the vehement objections of MIT faculty, students, and alumni. However, a 1917 decision by the Massachusetts Supreme Judicial Court effectively put an end to the merger scheme.

    In 1916, the Massachusetts Institute of Technology (US) administration and the MIT charter crossed the Charles River on the ceremonial barge Bucentaur built for the occasion, to signify MIT’s move to a spacious new campus largely consisting of filled land on a one-mile-long (1.6 km) tract along the Cambridge side of the Charles River. The neoclassical “New Technology” campus was designed by William W. Bosworth and had been funded largely by anonymous donations from a mysterious “Mr. Smith”, starting in 1912. In January 1920, the donor was revealed to be the industrialist George Eastman of Rochester, New York, who had invented methods of film production and processing, and founded Eastman Kodak. Between 1912 and 1920, Eastman donated $20 million ($236.6 million in 2015 dollars) in cash and Kodak stock to MIT.

    Curricular reforms

    In the 1930s, President Karl Taylor Compton and Vice-President (effectively Provost) Vannevar Bush emphasized the importance of pure sciences like physics and chemistry and reduced the vocational practice required in shops and drafting studios. The Compton reforms “renewed confidence in the ability of the Institute to develop leadership in science as well as in engineering”. Unlike Ivy League schools, Massachusetts Institute of Technology (US) catered more to middle-class families, and depended more on tuition than on endowments or grants for its funding. The school was elected to the Association of American Universities (US)in 1934.

    Still, as late as 1949, the Lewis Committee lamented in its report on the state of education at Massachusetts Institute of Technology (US) that “the Institute is widely conceived as basically a vocational school”, a “partly unjustified” perception the committee sought to change. The report comprehensively reviewed the undergraduate curriculum, recommended offering a broader education, and warned against letting engineering and government-sponsored research detract from the sciences and humanities. The School of Humanities, Arts, and Social Sciences and the MIT Sloan School of Management were formed in 1950 to compete with the powerful Schools of Science and Engineering. Previously marginalized faculties in the areas of economics, management, political science, and linguistics emerged into cohesive and assertive departments by attracting respected professors and launching competitive graduate programs. The School of Humanities, Arts, and Social Sciences continued to develop under the successive terms of the more humanistically oriented presidents Howard W. Johnson and Jerome Wiesner between 1966 and 1980.

    Massachusetts Institute of Technology (US)‘s involvement in military science surged during World War II. In 1941, Vannevar Bush was appointed head of the federal Office of Scientific Research and Development and directed funding to only a select group of universities, including MIT. Engineers and scientists from across the country gathered at Massachusetts Institute of Technology (US)’s Radiation Laboratory, established in 1940 to assist the British military in developing microwave radar. The work done there significantly affected both the war and subsequent research in the area. Other defense projects included gyroscope-based and other complex control systems for gunsight, bombsight, and inertial navigation under Charles Stark Draper’s Instrumentation Laboratory; the development of a digital computer for flight simulations under Project Whirlwind; and high-speed and high-altitude photography under Harold Edgerton. By the end of the war, Massachusetts Institute of Technology (US) became the nation’s largest wartime R&D contractor (attracting some criticism of Bush), employing nearly 4000 in the Radiation Laboratory alone and receiving in excess of $100 million ($1.2 billion in 2015 dollars) before 1946. Work on defense projects continued even after then. Post-war government-sponsored research at MIT included SAGE and guidance systems for ballistic missiles and Project Apollo.

    These activities affected Massachusetts Institute of Technology (US) profoundly. A 1949 report noted the lack of “any great slackening in the pace of life at the Institute” to match the return to peacetime, remembering the “academic tranquility of the prewar years”, though acknowledging the significant contributions of military research to the increased emphasis on graduate education and rapid growth of personnel and facilities. The faculty doubled and the graduate student body quintupled during the terms of Karl Taylor Compton, president of Massachusetts Institute of Technology (US) between 1930 and 1948; James Rhyne Killian, president from 1948 to 1957; and Julius Adams Stratton, chancellor from 1952 to 1957, whose institution-building strategies shaped the expanding university. By the 1950s, Massachusetts Institute of Technology (US) no longer simply benefited the industries with which it had worked for three decades, and it had developed closer working relationships with new patrons, philanthropic foundations and the federal government.

    In late 1960s and early 1970s, student and faculty activists protested against the Vietnam War and Massachusetts Institute of Technology (US)’s defense research. In this period Massachusetts Institute of Technology (US)’s various departments were researching helicopters, smart bombs and counterinsurgency techniques for the war in Vietnam as well as guidance systems for nuclear missiles. The Union of Concerned Scientists was founded on March 4, 1969 during a meeting of faculty members and students seeking to shift the emphasis on military research toward environmental and social problems. Massachusetts Institute of Technology (US) ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the MIT (US) Lincoln Laboratory facility in 1973 in response to the protests. The student body, faculty, and administration remained comparatively unpolarized during what was a tumultuous time for many other universities. Johnson was seen to be highly successful in leading his institution to “greater strength and unity” after these times of turmoil. However six Massachusetts Institute of Technology (US) students were sentenced to prison terms at this time and some former student leaders, such as Michael Albert and George Katsiaficas, are still indignant about MIT’s role in military research and its suppression of these protests. (Richard Leacock’s film, November Actions, records some of these tumultuous events.)

    In the 1980s, there was more controversy at Massachusetts Institute of Technology (US) over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, Massachusetts Institute of Technology (US)’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    Massachusetts Institute of Technology (US) has kept pace with and helped to advance the digital age. In addition to developing the predecessors to modern computing and networking technologies, students, staff, and faculty members at Project MAC, the Artificial Intelligence Laboratory, and the Tech Model Railroad Club wrote some of the earliest interactive computer video games like Spacewar! and created much of modern hacker slang and culture. Several major computer-related organizations have originated at MIT since the 1980s: Richard Stallman’s GNU Project and the subsequent Free Software Foundation were founded in the mid-1980s at the AI Lab; the MIT Media Lab was founded in 1985 by Nicholas Negroponte and Jerome Wiesner to promote research into novel uses of computer technology; the World Wide Web Consortium standards organization was founded at the Laboratory for Computer Science in 1994 by Tim Berners-Lee; the MIT OpenCourseWare project has made course materials for over 2,000 Massachusetts Institute of Technology (US) classes available online free of charge since 2002; and the One Laptop per Child initiative to expand computer education and connectivity to children worldwide was launched in 2005.

    Massachusetts Institute of Technology (US) was named a sea-grant college in 1976 to support its programs in oceanography and marine sciences and was named a space-grant college in 1989 to support its aeronautics and astronautics programs. Despite diminishing government financial support over the past quarter century, MIT launched several successful development campaigns to significantly expand the campus: new dormitories and athletics buildings on west campus; the Tang Center for Management Education; several buildings in the northeast corner of campus supporting research into biology, brain and cognitive sciences, genomics, biotechnology, and cancer research; and a number of new “backlot” buildings on Vassar Street including the Stata Center. Construction on campus in the 2000s included expansions of the Media Lab, the Sloan School’s eastern campus, and graduate residences in the northwest. In 2006, President Hockfield launched the MIT Energy Research Council to investigate the interdisciplinary challenges posed by increasing global energy consumption.

    In 2001, inspired by the open source and open access movements, Massachusetts Institute of Technology (US) launched OpenCourseWare to make the lecture notes, problem sets, syllabi, exams, and lectures from the great majority of its courses available online for no charge, though without any formal accreditation for coursework completed. While the cost of supporting and hosting the project is high, OCW expanded in 2005 to include other universities as a part of the OpenCourseWare Consortium, which currently includes more than 250 academic institutions with content available in at least six languages. In 2011, Massachusetts Institute of Technology (US) announced it would offer formal certification (but not credits or degrees) to online participants completing coursework in its “MITx” program, for a modest fee. The “edX” online platform supporting MITx was initially developed in partnership with Harvard and its analogous “Harvardx” initiative. The courseware platform is open source, and other universities have already joined and added their own course content. In March 2009 the Massachusetts Institute of Technology (US) faculty adopted an open-access policy to make its scholarship publicly accessible online.

    Massachusetts Institute of Technology (US) has its own police force. Three days after the Boston Marathon bombing of April 2013, MIT Police patrol officer Sean Collier was fatally shot by the suspects Dzhokhar and Tamerlan Tsarnaev, setting off a violent manhunt that shut down the campus and much of the Boston metropolitan area for a day. One week later, Collier’s memorial service was attended by more than 10,000 people, in a ceremony hosted by the Massachusetts Institute of Technology (US) community with thousands of police officers from the New England region and Canada. On November 25, 2013, Massachusetts Institute of Technology (US) announced the creation of the Collier Medal, to be awarded annually to “an individual or group that embodies the character and qualities that Officer Collier exhibited as a member of the Massachusetts Institute of Technology (US) community and in all aspects of his life”. The announcement further stated that “Future recipients of the award will include those whose contributions exceed the boundaries of their profession, those who have contributed to building bridges across the community, and those who consistently and selflessly perform acts of kindness”.

    In September 2017, the school announced the creation of an artificial intelligence research lab called the MIT-IBM Watson AI Lab. IBM will spend $240 million over the next decade, and the lab will be staffed by MIT and IBM scientists. In October 2018 MIT announced that it would open a new Schwarzman College of Computing dedicated to the study of artificial intelligence, named after lead donor and The Blackstone Group CEO Stephen Schwarzman. The focus of the new college is to study not just AI, but interdisciplinary AI education, and how AI can be used in fields as diverse as history and biology. The cost of buildings and new faculty for the new college is expected to be $1 billion upon completion.

    The Caltech/MIT Advanced aLIGO (US) was designed and constructed by a team of scientists from California Institute of Technology (US), Massachusetts Institute of Technology (US), and industrial contractors, and funded by the National Science Foundation (US) .

    Caltech /MIT Advanced aLigo

    It was designed to open the field of gravitational-wave astronomy through the detection of gravitational waves predicted by general relativity. Gravitational waves were detected for the first time by the LIGO detector in 2015. For contributions to the LIGO detector and the observation of gravitational waves, two Caltech physicists, Kip Thorne and Barry Barish, and Massachusetts Institute of Technology (US) physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also an Massachusetts Institute of Technology (US) graduate, designed the laser interferometric technique, which served as the essential blueprint for the LIGO.

    The mission of Massachusetts Institute of Technology (US) is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of The Massachusetts Institute of Technology community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

     
  • richardmitnick 9:10 am on September 11, 2020 Permalink | Reply
    Tags: "Machine-learning helps sort out massive materials' databases", , , , MOFs-Metal-organic frameworks, Scientific Archeology-identifying material related previously published.   

    From École Polytechnique Fédérale de Lausanne: “Machine-learning helps sort out massive materials’ databases” 


    From École Polytechnique Fédérale de Lausanne

    11.09.20
    Nik Papageorgiou

    1
    EPFL
    EPFL and MIT scientists have used machine-learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.

    Metal-organic frameworks (MOFs) are a class of materials that contain nano-sized pores. These pores give MOFs record-breaking internal surface areas, which can measure up to 7,800 m^2 in a single gram of material. As a result, MOFs are extremely versatile and find multiple uses: separating petrochemicals and gases, mimicking DNA, producing hydrogen, and removing heavy metals, fluoride anions, and even gold from water are just a few examples.

    Because of their popularity, material scientists have been rapidly developing, synthesizing, studying, and cataloguing MOFs. Currently, there are over 90,000 MOFs published, and the number grows every day. Though exciting, the sheer number of MOFs is actually creating a problem: “If we now propose to synthesize a new MOF, how can we know if it is truly a new structure and not some minor variation of a structure that has already been synthesized?” asks Professor Berend Smit at EPFL Valais-Wallis, which houses a major chemistry department.

    To address the issue, Smit teamed up with Professor Heather J. Kulik at MIT, and used machine learning to develop a “language” for comparing two materials and quantifying the differences between them. The study is published in Nature Communications.

    Armed with their new “language”, the researchers set off to explore the chemical diversity in MOF databases. “Before, the focus was on the number of structures,” says Smit. “But now, we discovered that the major databases have all kinds of bias towards particular structures. There is no point in carrying out expensive screening studies on similar structures. One is better off in carefully selecting a set of very diverse structures, which will give much better results with far fewer structures.”

    Another interesting application is “scientific archeology”: The researchers used their machine-learning system to identify the MOF structures that, at the time of the study, were published as very different from the ones that are already known.

    “So we now have a very simple tool that can tell an experimental group how different their novel MOF is compared to the 90,000 other structures already reported,” says Smit.

    See the full article here .

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