Life and intelligence in the universe from nanobiological principles: A survey and budget of concepts and perspectives

A View from the Inside: Complexity in the Atomic Scale Ordering of Supported Metal Nanoparticles

“…78 Similarly, the degeneracies of the TR2 and TR3 paths were related to that of the TR1 path in the fit (Table 5). Finally, the third cumulant, σ (3) , was added to the list of variables for the 1NN path to account for the temperaturedependent and, possibly, size-dependent asymmetry of the 1NN pair distance distribution function. Figure 8 presents the theoretical EXAFS fits of the data collected for all the samples and the Pt metal foil at 200 K. The fit results for the coordination numbers of the nearest neighboring shells, first through the fifth, are summarized in the Table 5.…”

“…The EXAFS signal, χ(k), which is the sum of all contributions, χ i (k), from groups of atoms that lie at approximately equal distances from the absorbing atom (i.e., the ith shell) was adjusted by applying the EXAFS equation, written in the following extended form: 72 where k is the photoelectron wavenumber, f i eff (k) and δ i (k) are the photoelectron scattering-path amplitude and phase, respectively, S 0 2 is the passive electron reduction factor, R i is the effective half-path-length (which is equal to the interatomic distance for single-scattering paths),σ i 2 (discussed further below) is the mean-square deviation in R i , σ i (3) is the third cumulant, and λ i (k) is the photoelectron mean free path. The computer code FEFFIT was used to fit theoretical EXAFS calculated with FEFF6 to the experimental χ(k) data.…”

“…The ideas of complexity are perhaps best and most powerfully illustrated by the examples presented in biology. Living systems are adaptive − and demonstrate a hierarchical organization of structure and function manifested over many entangled length scales. − The assembly seen in these systems, one sensitively coupled to dissipative processes, leverages patterns established by self-assembly with structural organizations that result strictly on the basis of underlying dynamics. , It is not altogether surprising, given the sophistication and beauty of these biologically derived inspirations, that the focus of research on complex chemical systems has come to rest on the structures and dynamics seen in extended systems (e.g., supramolecular assemblies, − biomimetic systems, − complex quantum systems, − and granular materials , ). Such models might be taken to suggest that an implicit correlation exists between the size of an assembly and the degrees of freedom that might be embedded in its organization (with increasing possibilities for complex behavior following directly from this latter aspect).…”

“…1 The ideas of complexity are perhaps best and most powerfully illustrated by the examples presented in biology. Living systems are adaptive [2][3][4] and demonstrate a hierarchical organization of structure and function manifested over many entangled length scales. [3][4][5][6] The assembly seen in these systems, one sensitively coupled to dissipative processes, 7 leverages patterns established by self-assembly 8 with structural organizations that result strictly on the basis of underlying dynamics.…”

“…Living systems are adaptive [2][3][4] and demonstrate a hierarchical organization of structure and function manifested over many entangled length scales. [3][4][5][6] The assembly seen in these systems, one sensitively coupled to dissipative processes, 7 leverages patterns established by self-assembly 8 with structural organizations that result strictly on the basis of underlying dynamics. 7,8 It is not altogether surprising, given the sophistica- tion and beauty of these biologically derived inspirations, that the focus of research on complex chemical systems has come to rest on the structures and dynamics seen in extended systems (e.g., supramolecular assemblies, [9][10][11] biomimetic systems, [12][13][14] complex quantum systems, [15][16][17][18] and granular materials 19,20 ).…”