Nanostructures have attracted huge interest as a rapidly growing class of materials for many applications. Several techniques have been used to characterize the size, crystal structure, elemental composition and a variety of other physical properties of nanoparticles. In several cases, there are physical properties that can be evaluated by more than one technique. Different strengths and limitations of each technique complicate the choice of the most suitable method, while often a combinatorial characterization approach is needed. In addition, given that the significance of nanoparticles in basic research and applications is constantly increasing, it is necessary that researchers from separate fields overcome the challenges in the reproducible and reliable characterization of nanomaterials, after their synthesis and further process (e.g. annealing) stages. The principal objective of this review is to summarize the present knowledge on the use, advances, advantages and weaknesses of a large number of experimental techniques that are available for the characterization of nanoparticles. Different characterization techniques are classified according to the concept/group of the technique used, the information they can provide, or the materials that they are destined for. We describe the main characteristics of the techniques and their operation principles and we give various examples of their use, presenting them in a comparative mode, when possible, in relation to the property studied in each case.

/pdf/characterization-techniques-for-nanoparticles-comparison-and-2ubze3ehrc.pdf

Characterization techniques for nanoparticles: comparison and complementarity upon studying nanoparticle properties

Self-assembly of particles into long-range, three-dimensional, ordered superstructures is crucial for the design of a variety of materials, including plasmonic sensing materials, energy or gas storage systems, catalysts and photonic crystals. Here, we have combined experimental and simulation data to show that truncated rhombic dodecahedral particles of the metal-organic framework (MOF) ZIF-8 can self-assemble into millimetre-sized superstructures with an underlying three-dimensional rhombohedral lattice that behave as photonic crystals. Those superstructures feature a photonic bandgap that can be tuned by controlling the size of the ZIF-8 particles and is also responsive to the adsorption of guest substances in the micropores of the ZIF-8 particles. In addition, superstructures with different lattices can also be assembled by tuning the truncation of ZIF-8 particles, or by using octahedral UiO-66 MOF particles instead. These well-ordered, sub-micrometre-sized superstructures might ultimately facilitate the design of three-dimensional photonic materials for applications in sensing.

Self-assembly of polyhedral metal-organic framework particles into three-dimensional ordered superstructures.

We present a new numerical scheme to study systems of nonconvex, irregular, and punctured particles in an efficient manner. We employ this method to analyze regular packings of odd-shaped bodies, both from a nanoparticle and from a computational geometry perspective. Besides determining close-packed structures for 17 irregular shapes, we confirm several conjectures for the packings of a large set of 142 convex polyhedra and extend upon these. We also prove that we have obtained the densest packing for both rhombicuboctahedra and rhombic enneacontrahedra and we have improved upon the packing of enneagons and truncated tetrahedra.

/pdf/dense-regular-packings-of-irregular-nonconvex-particles-49kunfmsj1.pdf

Dense Regular Packings of Irregular Nonconvex Particles

We generate maximally random jammed (MRJ) packings of the four nontiling Platonic solids (tetrahedra, octahedra, dodecahedra, and icosahedra) using the adaptive-shrinking-cell method [S. Torquato and Y. Jiao, Phys. Rev. E 80, 041104 (2009)]. Such packings can be viewed as prototypical glasses in that they are maximally disordered while simultaneously being mechanically rigid. The MRJ packing fractions for tetrahedra, octahedra, dodecahedra, and icosahedra are, respectively, 0.763±0.005, 0.697±0.005, 0.716±0.002, and 0.707±0.002. We find that as the number of facets of the particles increases, the translational order in the packings increases while the orientational order decreases. Moreover, we show that the MRJ packings are hyperuniform (i.e., their infinite-wavelength local-number-density fluctuations vanish) and possess quasi-long-range pair correlations that decay asymptotically with scaling r(-4). This provides further evidence that hyperuniform quasi-long-range correlations are a universal feature of MRJ packings of frictionless particles of general shape. However, unlike MRJ packings of ellipsoids, superballs, and superellipsoids, which are hypostatic, MRJ packings of the nontiling Platonic solids are isostatic. We provide a rationale for the organizing principle that the MRJ packing fractions for nonspherical particles with sufficiently small asphericities exceed the corresponding value for spheres (∼0.64). We also discuss how the shape and symmetry of a polyhedron particle affects its MRJ packing fraction.

https://link.aps.org/accepted/10.1103/PhysRevE.84.041309

Maximally random jammed packings of Platonic solids: hyperuniform long-range correlations and isostaticity.

This paper discusses the Monte Carlo and Molecular Dynamics methods. Both methods are, in principle, simple. However, simple does not mean risk-free. In the literature, many of the pitfalls in the field are mentioned, but usually as a footnote --and these footnotes are scattered over many papers. The present paper focuses on the “dark side” of simulation: it is one big footnote. I should stress that “dark”, in this context, has no negative moral implication. It just means: under-exposed.

Simulations: The dark side

We present an efficient and robust method based on Monte Carlo simulations for predicting crystal structures at finite temperature. We apply this method, which is surprisingly easy to implement, to a variety of systems, demonstrating its effectiveness for hard, attractive, and anisotropic interactions, binary mixtures, semi-long-range soft interactions, and truly long-range interactions where the truly long-range interactions are treated using Ewald sums. In the case of binary hard-sphere mixtures, star polymers, and binary Lennard-Jones mixtures, the crystal structures predicted by this algorithm are consistent with literature, providing confidence in the method. Finally, we predict new crystal structures for hard asymmetric dumbbell particles, bowl-like particles and hard oblate cylinders and present the phase diagram for the oblate cylinders based on full free energy calculations.

/pdf/efficient-method-for-predicting-crystal-structures-at-finite-1eobe9bb8r.pdf

Efficient method for predicting crystal structures at finite temperature: variable box shape simulations.

Publisher's Note: Efficient Method for Predicting Crystal Structures at Finite Temperature: Variable Box Shape Simulations

Publisher's Note: Efficient Method for Predicting Crystal Structures at Finite Temperature: Variable Box Shape Simulations [Phys. Rev. Lett. 103, 188302 (2009)]

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Efficient method for predicting crystal structures at finite temperature: variable box shape simulations.

Publisher's Note: Efficient Method for Predicting Crystal Structures at Finite Temperature: Variable Box Shape Simulations

Publisher's Note: Efficient Method for Predicting Crystal Structures at Finite Temperature: Variable Box Shape Simulations [Phys. Rev. Lett. 103, 188302 (2009)]