These simple liquid salts (single anion and cation) can be mixed with other salts (including inorganic salts) to form multicomponent ionic liquids. The asymmetry reduces the lattice energy of the crystalline structure and results in a low-melting-point salt. Mukesh Doble, Anil Kumar Kruthiventi, in Green Chemistry and Engineering, 2007 Ionic LiquidsĪn ionic liquid generally consists of a large nitrogen-containing organic cation and a smaller, inorganic anion. In the life sciences, this corresponds to simulating a protein by considering its constituent amino acids as the elementary entities. For example, if multiatom nanoblocks are used as units of assembly, it may not be necessary to explicitly simulate each atom within the block. Examples of the technologies in current use include Brownian dynamics, finite element analysis and computational fluid dynamics. On the other hand, dynamic mean field theory (DMFT) seems to be capable of successfully dealing with strongly correlated solids, and capable of predicting band gap transitions, for example.īeyond the capabilities of molecular dynamics, we are really into the meso- or microscale, in which it is not necessary to explicitly simulate each atom. Furthermore, the biological systems typically have to operate in the presence of bulk liquid water, which is still difficult to deal with because of its highly correlated nature. a ribosome) of a similar size are extremely difficult to simulate operationally because of relaxation modes at many different timescales, extending to tens of seconds or longer, because the structures are “soft”, diamondoid devices such as a gear train typically operate in the GHz frequency domain. This has been done extensively for the Feynman–Drexler diamondoid devices being considered as a way to realize productive nanosystems. Nevertheless, it is attractive that a nanodevice is small enough for it to be possible to explicitly simulate its operation with atomic resolution (molecular dynamics), using present-day computing resources. Similarly, molecular dynamics can be used to better understand physical properties of nanomaterials. On the other hand, if a materials formation process, such as a complex crystallization, is being simulated the material is likely to already exist, the purpose of the simulation being to better understand the formation process. For much of the work in nanodevices, it is not possible to give a general guarantee of the validity of this approach because no complete nanodevices of the type being simulated have as yet been constructed hence, the output of the simulations cannot be verified by comparison with experiment. A general weakness of such atomic simulations is that they use predefined empirical potentials, with parameters adjusted by comparing predictions of the model with available experimental data. Where m i is the mass of the ith atom and V is the interatomic potential.
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