Feynman Prize in Nanotechnology

Last updated
Feynman Prize in Nanotechnology
Awarded forExperimental and theoretical advancements in nanotechnology research
CountryUnited States
Presented by Foresight Institute
First awarded1993
Website www.foresight.org/prize

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.

Contents

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

YearLaureateInstitutionScope 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

YearLaureateInstitutionScope 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 AngelesIntegration 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 AngelesSynthesis 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 LaboratoryImaging 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 TechnologyMolecular 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

YearLaureateInstitutionScope 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 TechnologyModeling 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, BerkeleyModeling 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 ResearchTheoretical 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 UniversityModeling 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 UniversityTools 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 UniversityFunctional 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]
2023Alexandre TkatchenkoUniversity of LuxembourgFor 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

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