News
Spectroscopy in a quantum dot Along with detecting single molecules, collecting data on quantum dots remains a significant challenge. Quantum dots are solid-state crystalline structures so small that their electronic wave function is completely localized and their energy spectrum is quantized. As a result, optical linewidths of these structures approach the natural linewidths expected from radiative lifetimes. Spectroscopic studies of single quantum dots have yieldedfinestructure and hyperfine shifts, for example. To date, however, only the electronic spectra of these structures have been reported. D. Gammon and colleagues at the Naval Research Laboratory described resonant Raman and NMR spectroscopies of single gallium arsenide quantum dots. The experiments had a lateral spatial resolution of ~ 10 nm and probed a volume 100,000-fold smaller than that of previous semiconductor nuclear spectroscopic studies. Individual dots were observed with resonant Raman by exciting and detecting light through apertures ranging in diameter from 0.2 to 25 um. Samples were maintained at 6 K. Under the appropriate optical resonance conditions, the optical phonon Raman spectrum of individual quantum dots was measured. In the NMR experiments, the sample was inserted into a longitudinal magneticfieldof 1T aligned normal to the quantum well. The magneticfieldinteractions led to an Overhauser shift; by measuring the magnitude of that shift under NMR conditions it was possible to measure the NMR spectrum of the nuclei in an individual quantum dot. (Science 1197 277 85-888
Top spectrum shows longitudinal optical vibrations of the nuclei (phonons) from m quantum dott bottom is the conventional resonant Raman specttum. (Adapted with permission. Copyright 1197 American Association for the Advancement of Science.) 522 A
Smaller LEIS Electrochemical impedance spectroscopy (EIS) has been used to study the degradation of coated metals exposed to various environmental conditions. Interpretation of the data is difficult because these systems are complex and the impedance data are averaged over the whole exposed area, although the degradation occurs locally. In local EIS, a specially designed probe consisting of two platinum electrodes mounted in glass capillaries is used to determine the ac density from the potential gradients above the surface. Previously reported studies have used a relatively large probe, which has limited the spatial resolution. H. S. Isaacs and colleagues at the
Near-IR sorts through the trash The separation of plastic wastes is a major obstacle for their recycling. Ideally, an on-line technique would distinguish between different types of plastics. L.M.C. Buydens and colleagues at Catholic University of Nijmegen (The Netherlands) and Institute for Biochemical Sensor Research (Germany) haven't developed a technique to do that, but they demonstrated a macroscopic near-IR imaging technique for the on-line discrimination of plastic and non-plastic wastes. Near-IR images collected with an interference filter wheel and an InSb focal plane array detector lyzed by linear discriminant analysis (LDA) which was used as a pattern recognition technique to classify the objects by material tvrje Spectra
Swedish Corrosion Institute and Brookhaven National Laboratory developed a much smaller LEIS probe that uses two 10-um platinum microelectrodes,
Schematic of the LEIS system. (Adapted mth permission. Copyright 1997 The Electrochemical Society.)
were collected over six wavelength regions. The image database was constructed using images of 40 waste objects—17 plastics and 23 nonplastics. The LDA model contained three classes—plastic, non-plastic, and background. The calibration was applied to the discrimination of a plastic (polyethyleneterephthalate fragment) waste object from a non-plastic (a folded cotton sock) waste object. To overcome difficulties from shadow contributions to the images, artifacts the model was not trained for the researchers needed to add a fourth class for shadows The researchers differentiated between the plastic and non-plastic. To apply this technique to discrimination of plastics from one another, the system will need to incorporate more wavelength regions or narrower filter widths. (Appl. Spectrosc. 1997,51,856-65)
Images of the plastic (left) and non-plastic (right) waste objects as classified by the four-class LDA model. Black represents plastic material, light gray represents background, and medium gray represents non-plastic material. (Adapted with permission. Copyright 1997 Society for Applied Spectroscopy.)
Analytical Chemistry News & Features, September 1, 1997
