TiO2 has attracted tremendous research interest for photocatalytic water splitting, solar hydrogen generation, environmental pollution removal, dye-sensitized solar cells, lithium-ion batteries, supercapacitors, and field emission. Microwave absorption materials (MAMs) play important roles in many military (e.g., the stealth coating on the B-2 bomber) and civil (e.g., telecommunications, noise reduction, information security, signal, and data protection) applications. However, TiO2 is not a good MAM due to its poor absorption in the microwave region. Here, we report that via hydrogenation excellent and tunable microwave absorption is achieved with hydrogenated TiO2 nanocrystals. After hydrogenation, 4.3x and 103x improvements have been obtained in storing and dissipating the electric energy of the microwave electromagnetic field. Their permittivity values are higher than those of the current carbonaceous MAMs. Instead of relying on the dipole rotation or ferromagnetic resonance mechanisms for traditional MAMs, the hydrogenated TiO2 nanocrystals work as good MAMs based on a newly proposed collective-movement-of-interfacial-dipole (CMID) mechanism. Although there is still no direct physical evidence of the interface effects of the CMID mechanism, the CMID as a hypothesis at this point successfully explained the origin of the enhanced microwave absorption of the hydrogenated TiO2 nanoparticles. This study thus may open new applications for TiO2 nanocrystals and also stimulate new approaches for new MAM development.

In this series of articles, a method is presented that performs (semi)quantitative phase analysis for nanocrystalline transmission electron microscope samples from selected area electron diffraction (SAED) patterns. Volume fractions and degree of fiber texture are determined for the nanocrystalline components. The effect of the amorphous component is minimized by empirical background interpolation. First, the two-dimensional SAED pattern is converted into a one-dimensional distribution similar to X-ray diffraction. Volume fractions of the nanocrystalline components are determined by fitting the spectral components, calculated for the previously identified phases with a priori known structures. These Markers are calculated not only for kinematic conditions, but the Blackwell correction is also applied to take into account dynamic effects for medium thicknesses. Peak shapes and experimental parameters (camera length, etc.) are refined during the fitting iterations. Parameter space is explored with the help of the Downhill-SIMPLEX. The method is implemented in a computer program that runs under the Windows operating system. Part I presented the principles, while part II elaborated current implementation. The present part III demonstrates the usage and efficiency of the computer program by numerous examples. The suggested experimental protocol should be of benefit in experiments aimed at phase analysis using electron diffraction methods.

We report kinetic Monte-Karlo (KMC) simulation of self-assembled synthesis of nanocrystals by physical vapor deposition (PVD), which is one of most flexible, efficient, and clean techniques to fabricate nanopatterns. In particular, self-assembled arrays of nanocrystals can be synthesized by PVD. However size, shape and density of self-assembled nanocrystals are highly sensitive to the process conditions such as duration of deposition, temperature, substrate material, etc. To efficiently synthesize nanocrystalline arrays by PVD, the process control factors should be understood in detail. KMC simulations of film deposition are an important tool for understanding the mechanisms of film deposition. In this paper, we report a KMC modeling that explicitly represents PVD synthesis of self-assembled nanocrystals. We study how varying critical process parameters such as deposition rate, duration, temperature, and substrate type affect the lateral 2D morphologies of self-assembled metallic islands on substrates, and compare our results with experimentally observed surface morphologies generated by PVD. Our simulations align well with experimental results reported in the literature.

This series of articles describes a method that performs (semi)quantitative phase analysis for nanocrystalline transmission electron microscope samples from selected area electron diffraction (SAED) patterns. Volume fractions of phases and their textures are obtained separately in the method. First, the two-dimensional SAED pattern is converted into an X-ray diffraction–like one-dimensional distribution. Volume fractions of the nanocrystalline components are determined by fitting the spectral components, calculated for the previously identified phases with a priori known structures. Blackman correction is also applied to take into account dynamic effects for medium grain sizes. Peak shapes and experimental parameters (camera length, etc.) are refined during the fitting iterations. Parameter space is explored with the help of the Downhill-SIMPLEX algorithm. Part I presented the principles, while Part II now elaborates current implementation, and Part III will demonstrate its usage by examples. The method is implemented in a computer program that runs under the Windows operating system on IBM PC compatible machines.

A method for phase analysis, similar to the Rietveld method in X-ray diffraction, was not developed for electron diffraction (ED) in the transmission electron microscope (TEM), mainly due to the dynamic nature of ED. Nowadays, TEM laboratories encounter many thin samples with grain size in the 1–30 nm range, not too far from the kinematic ED conditions. This article describes a method that performs (semi)quantitative phase analysis for nanocrystalline samples from selected area electron diffraction (SAED) patterns. Fractions of the different nanocrystalline components are determined from rotationally symmetric ring patters. Both randomly oriented nanopowders and textured nanopowders, observed from the direction of the texture axis produce such SAED patterns. The textured fraction is determined as a separate component by fitting the spectral components, calculated for the previously identified phases with a priori known structures, to the measured distribution. The Blackman correction is applied to the set of kinematic diffraction lines to take into account dynamic effects for medium grain size. Parameters of the peak shapes and the other experimental parameters are refined by exploring the parameter space with the help of the Downhill-SIMPLEX. Part I presents the principles, while future publication of Parts II and III will elaborate on current implementation and will demonstrate its usage by examples, respectively.

Recent results have demonstrated that hybrid photovoltaic cells based on a blend of inorganic nanocrystals and polymers possess significant potential for low-cost, scalable solar power conversion. Colloidal semiconductor nanocrystals, like polymers, are solution processable and chemically synthesized, but possess the advantageous properties of inorganic semiconductors such as a broad spectral absorption range and high carrier mobilities. Significant advances in hybrid solar cells have followed the development of elongated nanocrystal rods and branched nanocrystals, which enable more effective charge transport. The incorporation of these larger nanostructures into polymers has required optimization of blend morphology using solvent mixtures. Future advances will rely on new nanocrystals, such as cadmium telluride tetrapods, that have the potential to enhance light absorption and further improve charge transport. Gains can also be made by incorporating application-specific organic components, including electroactive surfactants which control the physical and electronic interactions between nanocrystals and polymer.

This article is an edited transcript based on the David Turnbull Lecture given by Ellen D. Williams of the University of Maryland on December 2, 2003, at the Materials Research Society Fall Meeting in Boston.Williams received the award for “groundbreaking research on the atomic-scale science of surfaces and for leadership, writing, teaching, and outreach that convey her deep understanding of and enthusiasm for materials research.” This article focuses on the special properties of small structures that provide much of the exciting potential of nanotechnology.One aspect of small structures—their susceptibility to thermal fluctuations—may create or necessitate new ways of exploiting nanostructures.The advent of scanned probe imaging techniques created new opportunities for observing and understanding such structural fluctuations and the related evolution of nanostructure.Direct observations show that it is relatively easy for large numbers of atoms—the kinds of numbers that are present in nanoscale structures—to pick up and move about on the surface cooperatively with substantial impact on nano-to micron-scale structures.Such labile evolution of structure can be predicted quantitatively by using length-scale bridging techniques of statistical mechanics coupled with scanned probe observations of structural and temporal distributions.The same measurements also provide direct information about the stochastic paths of structural fluctuations that can be used outside of the traditional thermodynamic framework.Future work involves moving beyond the classical thermodynamic picture to assess the impact that the stochastic behavior has on the physical properties of individual nanostructures.

The following article is an edited transcript based on the MRS Medalist presentation given by C. Jeffrey Brinker (Sandia National Laboratories and the University of New Mexico) on December 3, 2003, at the Materials Research Society Fall Meeting in Boston. Brinker received the Medal for “his pioneering application of principles of sol-gel chemistry to the self-assembly of functional nanoscale materials.” Nature combines hard and soft materials, often in hierarchical architectures, to obtain synergistic, optimized properties with proven, complex functionalities. Emulating natural designs in robust engineering materials using efficient processing approaches represents a fundamental challenge to materials chemists. This presentation reviews progress on understanding so-called evaporation-induced silica/surfactant self-assembly (EISA) as a simple, general means of preparing porous thin-film nanostructures. Such porous materials are of interest for membranes, low-dielectric-constant (low-k) insulators, and even ‘“nano-valves” that open and close in response to an external stimulus. EISA can also be used to simultaneously organize hydrophilic and hydrophobic precursors into hybrid nanocomposites that are optically or chemically polymerizable, patternable, or adjustable.