Feynman Prize in Nanotechnology
The Feynman Prize in Nanotechnology is an award given by the Foresight Institute for significant advances in nanotechnology. Two prizes are awarded annually, in the categories of experimental and theoretical work. There is also a separate challenge award for making a nanoscale robotic arm and 8-bit adder.
Feynman Prize in Nanotechnology | |
---|---|
Awarded for | Experimental and theoretical advancements in nanotechnology research |
Country | United States |
Presented by | Foresight Institute |
First awarded | 1993 |
Website | www |
Overview
The Feynman Prize consists of annual prizes in experimental and theory categories, as well as a one-time challenge award. They are awarded by the Foresight Institute, a nanotechnology advocacy organization. The prizes are named in honor of physicist Richard Feynman, whose 1959 talk There's Plenty of Room at the Bottom is considered by nanotechnology advocates to have inspired and informed the start of the field of nanotechnology.[1]
The annual Feynman Prize in Nanotechnology is awarded for pioneering work in nanotechnology, towards the goal of constructing atomically precise products through molecular machine systems. Input on prize candidates comes from both Foresight Institute personnel and outside academic and commercial organizations. The awardees are selected mainly by an annually changing body of former winners and other academics.[1] The prize is considered prestigious,[1][2] and authors of one study considered it to be reasonably representative of notable research in the parts of nanotechnology under its scope.[1]
The separate Feynman Grand Prize is a $250,000 challenge award to the first persons to create both a nanoscale robotic arm capable of precise positional control, and a nanoscale 8-bit adder, conforming to given specifications. It is intended to stimulate the field of molecular nanotechnology.[3][4][5]
History
The Feynman Prize was instituted in the context of Foresight Institute co-founder K. Eric Drexler's advocacy of funding for molecular manufacturing.[1] The prize was first given in 1993. Before 1997, one prize was given biennially. From 1997 on, two prizes were given each year in theory and experimental categories.[1] By awarding these prizes early in the history of the field, the prize increased awareness of nanotechnology and influenced its direction.[6]: 60 [7][8]
The Grand Prize was announced in 1995 at the Fourth Foresight Conference on Molecular Nanotechnology and was sponsored by James Von Ehr and Marc Arnold.[9][10] In 2004, X-Prize Foundation founder Peter Diamandis was selected to chair the Feynman Grand Prize committee.[3]
Recipients
Single prize
Year | Laureate | Institution | Scope of work |
---|---|---|---|
1993 | Charles Musgrave | California Institute of Technology | Molecular modelling of atomically precise manufacturing[11][12] |
1995 | Nadrian C. Seeman | New York University | DNA nanotechnology[8][13][14] |
Experimental category
Year | Laureate | Institution | Scope of work |
---|---|---|---|
1997 | James K. Gimzewski | IBM Zurich Research Laboratory | Scanning probe microscopy for atomically precise manufacturing[6]: 55, 182 [15] |
Reto Schlittler | |||
Christian Joachim | CEMES/French National Centre for Scientific Research | ||
1998 | M. Reza Ghadiri | Scripps Research Institute | Molecular self-assembly[16][17] |
1999 | Phaedon Avouris | IBM Watson Research Center | Molecular scale electronics using carbon nanotubes[18][19][20] |
2000 | R. Stanley Williams | HP Labs | Switches for molecular scale electronics[20][21] |
Philip Kuekes | |||
James R. Heath | University of California, Los Angeles | ||
2001 | Charles M. Lieber | Harvard University | Synthesis and characterization of carbon nanotubes[20][22] |
2002 | Chad Mirkin | Northwestern University | Spherical nucleic acid nanoparticles[6]: 163 [20][23][24] |
2003 | Carlo Montemagno | University of California, Los Angeles | Integration of biological molecular motors with silicon devices[25] |
2004 | Homme Hellinga | Duke University | Atomically precise manufacturing[26] |
2005 | Christian Schafmeister | University of Pittsburgh | Synthesis of designed macromolecules[27][28] |
2006 | Erik Winfree | California Institute of Technology | DNA computing using algorithmic self-assembly[6]: 140 [29] |
Paul W. K. Rothemund | |||
2007 | J. Fraser Stoddart | University of California, Los Angeles | Synthesis and assembly of molecular machines[30] |
2008 | James Tour | Rice University | Synthesis of nanocars and other molecular machines[31] |
2009 | Yoshiaki Sugimoto | Osaka University | Non-contact atomic force microscopy for manipulation of single atoms[32][33] |
Masayuki Abe | |||
Oscar Custance | Japanese National Institute for Materials Science | ||
2010 | Masakazu Aono | MANA Center, Japanese National Institute for Materials Science | Scanning probe microscopy for manipulation of atoms[34] |
2011 | Leonhard Grill | Fritz Haber Institute of the Max Planck Society | Scanning probe microscopy for characterization and manipulation of molecules[35][36] |
2012 | Gerhard Meyer | IBM Zurich Research Laboratory | Imaging and manipulation of molecular orbitals using scanning probe microscopy[36][37] |
Leo Gross | |||
Jascha Repp | |||
2013 | Alexander Zettl | University of California, Berkeley | Nanoscale electromechanical systems[38] |
2014 | Joseph W. Lyding | University of Illinois at Urbana–Champaign | Hydrogen depassivation lithography using scanning tunneling microscopes[39] |
2015 | Michelle Y. Simmons | University of New South Wales | Fabrication of single-atom transistors[40][41] |
2016 | Franz J. Giessibl | University of Regensburg | Imaging and manipulation of individual atoms using scanning probe microscopy[42] |
2017 | William Shih | Harvard University | DNA nanotechnology[43] |
2018 | Christopher Lutz | IBM Almaden Research Center | Manipulating atoms and small molecules for data storage and computation[44] |
Andreas J. Heinrich | Center for Quantum Nanoscience, Institute for Basic Science | ||
2019 | Lulu Qian | California Institute of Technology | Molecular robotics, self-assembly of DNA structures, and biochemical circuits[45] |
2020 | Hao Yan | Arizona State University | Use of DNA as designer molecular building blocks for programmable molecular self-assembly.[46] |
2021 | Anne-Sophie Duwez | University of Liège | Developed tools and technologies to interface synthetic functional molecules with AFM to study their operation and her other single-molecule research.[47][48] |
2022 | Sergei V. Kalinin | University of Tennessee | Applications of machine learning and artificial intelligence in nanotechnology, atomic fabrication, and materials discovery via scanning transmission electron microscopy, as well as mesoscopic studies of electrochemical, ferroelectric, and transport phenomena via scanning probe microscopy.[49][50] |
2023 | James J. Collins | Massachusetts Institute of Technology | For pioneering work on synthetic gene circuits that launched the field of synthetic biology and has enabled the development of programmable biomolecular tools for the life sciences, medicine and nanobiotechnology.[51] |
Theory category
Year | Laureate | Institution | Scope of work |
---|---|---|---|
1997 | Charles Bauschlicher | NASA Ames Research Center | Computational nanotechnology[15][52] |
Stephen Barnard | |||
Creon Levit | |||
Glenn Deardorff | |||
Al Globus | |||
Jie Han | |||
Richard Jaffe | |||
Alessandra Ricca | |||
Marzio Rosi | |||
Deepak Srivastava | |||
H. Thuemmel | |||
1998 | Ralph C. Merkle | Zyvex | Molecular tools for atomically precise chemical reactions[16][17] |
Stephen Walch | ELORET Corporation/NASA Ames Research Center | ||
1999 | William A. Goddard III | California Institute of Technology | Modeling of molecular machines[18] |
Tahir Cagin | |||
Yue Qi | |||
2000 | Uzi Landman | Georgia Institute of Technology | Computational materials science for nanostructures[21] |
2001 | Mark A. Ratner | Northwestern University | Molecular scale electronics[22] |
2002 | Don Brenner | North Carolina State University | Molecular machines for molecular manufacturing[23][24] |
2003 | Marvin L. Cohen | University of California, Berkeley | Modeling of new materials[25] |
Steven G. Louie | |||
2004 | David Baker | University of Washington | Development of RosettaDesign[26] |
Brian Kuhlman | University of North Carolina, Chapel Hill | ||
2005 | Christian Joachim | French National Centre for Scientific Research | Theoretical tools and design principles for molecular machines[6]: 56 [27] |
2006 | Erik Winfree | California Institute of Technology | DNA computing[29] |
Paul W. K. Rothemund | |||
2007 | David A. Leigh | University of Edinburgh | Design and synthesis of molecular machines[30] |
2008 | George C. Schatz | Northwestern University | Modeling of dip-pen nanolithography, and of plasmon effects in metallic nanoparticles[31] |
2009 | Robert A. Freitas Jr. | Institute for Molecular Manufacturing | Mechanosynthesis and systems design of molecular machines[32] |
2010 | Gustavo E. Scuseria | Rice University | Tools for modeling of carbon nanostructures[34] |
2011 | Raymond Astumian | University of Maine | Molecular machines powered by Brownian motion[35][36] |
2012 | David Soloveichik | University of California, San Francisco | DNA computing using strand displacement cascades[37] |
2013 | David Beratan | Duke University | Functional supramolecular assemblies[38] |
2014 | Amanda Barnard | Australian Commonwealth Scientific and Industrial Research Organisation | Carbon nanostructure structure-function relationships[39][53] |
2015 | Markus J. Buehler | Massachusetts Institute of Technology | Mechanical simulations of materials[40] |
2016 | Bartosz Grzybowski | Ulsan National Institute of Science and Technology | Modeling of the outcomes of organic reactions[42] |
2017 | Giovanni Zocchi | University of California, Los Angeles | Stress–strain analysis of soft nanoparticles[43] |
2018 | O. Anatole von Lilienfeld | University of Basel, now University of Vienna | Methods for fast quantum mechanical modelling[44] |
2019 | Giulia Galli | University of Chicago | The development of theoretical and computational methods to predict and design, from first principles, the properties of nanostructured materials.[45] |
2020 | Massimiliano Di Ventra | University of California, San Diego | Quantum transport in nanoscale and atomic systems; prediction of nanoscale phenomena which were later verified experimentally, studied memory effects in materials and devices.[54] |
2021 | Kendall N. Houk | UCLA | Quantum mechanical and molecular dynamics simulations which have elucidated structural and dynamical features of synthetic nanomachines.[47][55] |
2022 | James R. Chelikowsky | University of Texas | Pioneered the use of computational approaches to understand and predict the properties of materials at the nanoscale.[49][56] |
2023 | Alexandre Tkatchenko | University of Luxembourg | For pioneering the development of methods that seamlessly merge quantum mechanics, statistical mechanics, and machine learning to unravel the intricacies of complex molecules and materials.[57] |
See also
- Kavli Prize in Nanoscience
- IEEE Pioneer Award in Nanotechnology
- ISNSCE Nanoscience Award
- UPenn NBIC Award for Research Excellence in Nanotechnology
- List of physics awards
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