The method overcomes a longstanding timing gap in modeling nanometer-scale materials and many other physical, chemical and biological systems at atomic and molecular levels.
The new mathematical technique* can significantly improve modeling of atomic-scale processes that unfold over time, such as vibrations in a crystal. Conventional molecular dynamics (MD) techniques can accurately model processes that occur in increments measured in picoseconds to femtoseconds (trillionths to quadrillionths of a second). Other techniques can be used over longer periods to model bulk materials but not at the molecular level.
The new NIST technique can access these longer time scales—in the critical range from nanoseconds to microseconds (billionths to millionths of a second)—at the molecular level. Scientists can now measure and understand what happens at key points in time that were not previously accessible, and throughout the full spectrum of time scales of interest in MD, says developer Vinod Tewary.
Modeling of material properties and physical processes is a valuable aid and supplement to theoretical and experimental studies, in part because experiments are very difficult at the nanoscale. MD calculations are usually based on the physics of individual atoms or molecules. This traditional approach is limited not only by time scale, but also by system size.
It cannot be extended to processes involving thousands of atoms or more because today’s computers—even supercomputers—cannot handle the billions of time steps required, Tewary says. By contrast, his new method incorporates a “Green’s function,” a mathematical approach that can calculate the condition of a very large system over flexible time scales in a single step. Thus, it overcomes the system size problem as well as the timing gap.
Tewary illustrated the new technique on two problems. He showed how a pulse propagating through a string of atoms, initiated by moving the middle atom, could be modeled for just a few femtoseconds with conventional MD, whereas the NIST method works for several microseconds. Tewary also calculated how ripples propagate in 1,100 carbon atoms in a sheet of graphene over periods up to about 45 microseconds, a problem that could not be solved previously. Normally thought of as a static flat sheet, the atoms in graphene actually must undulate somehow to remain stable, and the new technique shows how these ripples propagate. (See accompanying image and movie). Consisting entirely of carbon atoms, graphene is a recently discovered honeycomb crystal material that may be an outstanding conductor for wires and other components in nanoscale electronics.
The new NIST technique is expected to enable modeling of many other processes that occur at time scales of nano- to microseconds, such as formation and growth of defects, conduction of heat, diffusion and radiation damage in materials. The technique could improve results in many different fields, from modeling of new nanotechnologies in the design stage to simulating the radiation damage from a “dirty bomb” over time.
NIST researchers plan to write a software program encoding the new technique to make it available to other users.
* V.K. Tewary. Extending time scale in molecular dynamics simulations: propagation of ripples in graphene. Physical Review B, Vol. 80, No. 16.. Published online Oct. 22, 2009.
Laura Ost | Newswise Science News
Tracing aromatic molecules in the early universe
23.03.2017 | University of California - Riverside
New study maps space dust in 3-D
23.03.2017 | DOE/Lawrence Berkeley National Laboratory
Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.
The results will be published on March 22 in the journal „Astronomy & Astrophysics“.
Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...
Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.
Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...
In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to simulate these confined natural conditions in artificial vesicles for the first time. As reported in the academic journal Small, the results are offering better insight into the development of nanoreactors and artificial organelles.
Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to...
20.03.2017 | Event News
14.03.2017 | Event News
07.03.2017 | Event News
23.03.2017 | Life Sciences
23.03.2017 | Power and Electrical Engineering
23.03.2017 | Earth Sciences