Computational Science in Nanometrology
Sharon C. Glotzer, University of Michigan
Precise, accurate and reliable measurement capabilities are required in all areas of science
and engineering. Achieving such capabilities at the nanoscale is especially challenging
due to uncertainties and noise inherent to the measurement process at this scale.
However, designing, fabricating and manipulating nanoscale components to make
targeted materials and devices from the bottom up will require precise, accurate, and
reliable measurements of:
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Forces between nanoscale components - E.g., between quantum dots in organic
and aqueous solution for nanosensors; nanotubes and organic molecules on silicon
or gold surfaces for nanoelectronics; biological ligands and nanocrystalline
surfaces for nanobiomaterials, etc.
Nanoscale features of structures fabricated at the nanoscale and/or via nanoscale
Components - E.g. cylindrical or lamellae structures formed by the self-assembly
of functional nano building blocks; porosity, domain size, positional and
orientational arrangement of polymer-tethered, inorganic silica “nanocubes” used
for coatings or low-k dielectric materials; dispersion of nanoparticles in polymer
matrices and structure of polymers near nanoparticle surfaces, etc.
Time-dependent processes occurring at length scales ranging from angstroms to
Microns - E.g. dynamics of assembly as molecules and nano building blocks
organize into structures with positional and/or orientational order on increasing
larger length scales.
In all aspects of nanoscale measurement, reliable models based on sound, scientific
theories will be needed to interpret measurements, and simulations will be needed to test
these theories, validate measurements, and stand in for measurements not yet possible.
Indeed, in many instances computational predictions are currently more accurate, precise,
and reliable than experimental measurements, and in such cases simulations or first
principles calculations are carried out to validate the measurement.
Computational science has a critical role to play in nanometrology in (i) aiding the
interpretation of measurements at the nanoscale, (ii) providing fundamental information
and insight necessary for the development of nanometric tools and methodologies, (iii)
providing virtual measurements of nanoscale features or properties, and (iv) enabling
fast, global access to real and virtual nanoscale measurements. Already, the field of
computational science is contributing to revolutionary advances in nanoscale science and
engineering. In nanoscale metrology and instrumentation, major breakthroughs and
improvements in many key areas of computational science, mathematics and statistics
will be required over the next decade. For example:
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Order(N) methods to enable ab initio calculations on larger numbers of atoms
than is currently possible is required for the prediction of, e.g., effective forces,
structure, and optical, electronic, and mechanical properties as virtual
measurements or to validate experimental measurements.
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Acceleration algorithms are needed for significantly advancing timescales of
quantum and classical simulations for virtual measurements of electron transport,
self-assembly of nano building blocks, and electronic, optical, photonic,
mechanical and other properties of nanomaterials and nanodevices.
Increased accuracy, extensibility and transferability of classical force fields are
needed to simulate, e.g., the assembly of nanomaterials and interpret
measurements of structural evolution. Here there are particular challenges in
developing accurate force fields for hybrid materials such as biological-inorganic
and organic-inorganic nanocomposites.
Improved, public domain data-mining and database management tools are needed
for accessing and sharing both real and virtual measurements.
Public-domain statistical analysis tools are needed for interpreting and assessing
uncertainty and statistical correlations in real and virtual measurements.
Faster algorithms and hardware are needed for visualization, especially interactive
visualization of nanoscale structure and phenomena and computational steering of
virtual measurement methodologies.
Theoretical and mathematical methods such as homogenization for coarsegraining are required for the development of computationally tractable models
used in quantum mechanical and classical simulations of nanoscale phenomena,
and for the bridging of length and time scales for multiscale modeling and
simulation.
Computational methods must be devised to identify quantitative measures for
characterizing and monitoring structural order in nanoscale systems, to interpret
nanoscale characterization measurements and monitor nanofabrication and
nanomanufacturing processes.
Revolutionary improvements in high performance computing and access to fast
machines are critical for increasing the accuracy and precision of virtual
measurements from ab initio, molecular and mesoscale simulation. Concerted
improvements in algorithms, software, hardware (processor speed, memory
access, etc.), and middleware will all be required in this regard.
Revolutionary improvements in high-speed communications are required to
support increased inter-processor communication and data transfer for distributed
and parallel high performance computing; computational steering, interactive
visualization, data mining and manipulation, and database management.