Plasmonic enhancement of aqueous processed organic photovoltaics

Sodium tungsten bronze (Na_xWO₃) is a promising alternative plasmonic material to nanoparticulate gold due to its strong plasmonic resonances in both the visible and near-infrared (NIR) regions. Additional benefits include its simple production either as a bulk or a nanoparticle material at a relatively low cost. In this work, plasmonic Na_xWO₃ nanoparticles were introduced and mixed into the nanoparticulate zinc oxide electron transport layer of a water processed poly(3-hexylthiophene):phenyl-C₆₁-butyric acid methyl ester (P3HT:PC₆₁BM) nanoparticle (NP) based organic photovoltaic device (NP-OPV). The power conversion efficiency of NP-OPV devices with Na_xWO₃ NPs added was found to improve by around 35% compared to the control devices, attributed to improved light absorption, resulting in an enhanced short circuit current and fill factor.

Plasmonic Na_xWO₃ nanoparticles were introduced to aqueous processed organic photovoltaics with 35% device enhancement.

Anomalously strong plasmon resonances in aluminium bronze by modification of the electronic density-of-states

We use a combination of experimental measurements and density functional theory calculations to show that modification of the band structure of Cu by additions of Al causes an unexpected enhancement of the dielectric properties. The effect is optimized in alloys with Al contents between 10 and 15 at.% and would result in strong localized surface plasmon resonances at suitable wavelengths of light. This result is surprising as, in general, alloying of Cu increases its DC resistivity and would be expected to increase optical loss. The wavelengths for the plasmon resonances in the optimized alloy are significantly blue-shifted relative to those of pure Cu and provide a new material selection option for the range 2.2-2.8 eV.

The effect of vacancies on the optical properties of AuAl₂

AuAl2 is an intermetallic compound with a vivid purple colour attributable to a bulk plasmon energy in the visible part of the spectrum. However, the colour of as-deposited thin films is not as strong and only develops upon annealing. Density functional theory calculations of the dielectric function are presented for a variety of vacancy types and concentrations. The results support the view that the effect of annealing on colour is correlated with a reduction in concentration of Al vacancies. The effect of vacancies on the optical properties can be understood as arising from the complex interplay between interband transitions around the Fermi level and the plasmon energy.

First principles calculations of the optical and plasmonic response of Au alloys and intermetallic compounds

Pure Au is widely used in plasmonic applications even though its use is compromised by significant losses due to damping. There are some elements that are less lossy than Au (e.g. Ag or Al) but they will normally oxidize or corrode under ambient conditions. Here we examine whether alloying Au with a second element would be beneficial for plasmonic applications. In order to evaluate potential alternatives to pure Au, the density of states (DOS), dielectric function and plasmon quality factor have been calculated for alloys and compounds of Au with Al, Cd, Mg, Pd, Pt, Sn, Ti, Zn and Zr. Substitutional alloying of Au with Al, Cd, Mg and Zn was found to slightly improve the plasmonic response. Of the large number of intermetallic compounds studied, only AuAl2, Au3Cd, AuMg, AuCd and AuZn were found to be suitable for plasmonic applications.

Two-dimensional mapping of chemical information at atomic resolution

The simultaneous measurement of structural and chemical information at the atomic scale provides fundamental insights into the connection between form and function in materials science and nanotechnology. We demonstrate structural and chemical mapping in Bi(0.5) Sr(0.5) MnO3 using an aberration-corrected scanning transmission electron microscope. Two-dimensional mapping is made possible by an adapted method for fast acquisition of electron energy-loss spectra. The experimental data are supported by simulations, which help to explain the less intuitive features.

New developments in electron energy loss spectroscopy

In the electron microscope, spectroscopic signals such as the characteristic X-rays or the energy loss of the incident beam can provide an analysis of the local composition or electronic structure. Recent improvements in the energy resolution and sensitivity of electron spectrometers have improved the quality of spectra that can be obtained. Concurrently, the calculations used to simulate and interpret spectra have made major advances. These developments will be briefly reviewed. In recent years, the focus of analytical electron microscopy has moved away from single spectrum acquisition to mapping and imaging. In particular, the use of spectrum imaging (SI), where a full spectrum is acquired and stored at each pixel in the image is becoming widespread. A challenge for the application of spectrum imaging is the processing of such large datasets in order to extract the significant information. When we go beyond the mapping of composition and look to map bonding and electronic structure this becomes both more important and more difficult. Approaches to processing spectrum imaging data sets acquired using electron energy loss spectroscopy (EELS) will be explored in this paper.

Mapping chemical and bonding information using multivariate analysis of electron energy-loss spectrum images

Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) is used to obtain high-resolution information on the composition and the type of chemical bonding of materials. Spectrum imaging, where a full EEL spectrum is acquired and stored at each pixel in the image, gives an exact correlation of spatial and spectral features. However, determining and extracting the important spectral components from the large amount of information contained in a spectrum image (SI) can be difficult. This paper demonstrates that principal component analysis of EEL SIs can be used to extract chemically relevant components. With weighted or two-way scaled principal component analysis, both compositional and bonding information can be extracted. Mapping of the chemical variations in a partially reduced titanium dioxide sample and the orientation-dependent bonding in boron nitride and carbon nanotubes are given as examples.

Electron energy-loss near edge structure (ELNES) of InGaN quantum wells

Lasers and light-emitting diodes (LEDs) that emit in the blue to green region are often based on InxGa1-xN quantum well structures. Ionization edges in the electron energy-loss spectrum contain fine structures (called the energy-loss near edge structure (ELNES)) and provide information about the electronic structure. In this paper we compare the experimental and calculated ELNES for the N-K ionization edge of InxGa1-xN quantum wells. When the effects of the core-hole are included in the calculations, agreement between experimental and calculated spectra is very good. Strain has been shown to accentuate the effects of In on the ELNES and moves the ionization edge onset down in energy, relative to the other features. These results suggest that ELNES may provide an alternative method to lattice imaging to determine the presence of strain in this system.

Electron energy-loss near-edge structure -- a tool for the investigation of electronic structure on the nanometre scale

Electron energy-loss near-edge structure (ELNES) is a technique that can be used to measure the electronic structure (i.e. bonding) in materials with subnanometre spatial resolution. This review covers the theoretical principles behind the technique, the experimental procedures necessary to acquire good ELNES spectra, including potential artefacts, and gives examples relevant to materials science.

Quantification of boundary segregation in the analytical electron microscope

When studying equilibrium grain-boundary segregation using the small ( approximately 1 nm) electron probe of the scanning transmission electron microscope and X-ray energy dispersive spectroscopy, the assumptions made about the size and shape of the beam-specimen interaction volume may introduce errors in quantification of up to a factor of five. Comparisons between experimental segregation profiles and different theoretical models have shown that a Gaussian model for the electron distribution will provide the best description for the interaction volume. Calculations of minimum detectable segregation levels have shown that optimum sensitivity is not achieved in the thinnest samples or even with the smallest probe sizes. In addition, operating at 300 keV (rather than 100 keV) will halve the minimum detectable segregation level, assuming all other experimental conditions are equal. Rastering the electron probe over a fixed area while acquiring spectra improves the accuracy of quantification but at the price of reducing sensitivity by at least a factor of three.