We investigate the system of optically excited gold NPs in an ice matrix aiming to understand heat generation and melting processes at the nanoscale level. Along with the traditional fluorescence method, we introduce thermooptical spectroscopy based on phase transformation of a matrix. With this, we can not only measure optical response but also thermal response, that is, heat generation. After several recrystallization cycles, the nanoparticles are embedded into the ice film where the optical and thermal properties of the nanoparticles are probed. Spatial fluorescence mapping shows the locations of Au nanoparticles, whereas the time-resolved Raman signal of ice reveals the melting process. From the time-dependent Raman signals, we determine the critical light intensities at which the laser beam is able to melt ice around the nanoparticles. The melting intensity depends strongly on temperature and position. The position-dependence is especially strong and reflects a mesoscopic character of heat generation. We think that it comes from the fact that nanoparticles form small complexes of different geometry and each complex has a unique thermal response. Theoretical calculations and experimental data are combined to make a quantitative measure of the amount of heat generated by optically excited Au nanoparticles and agglomerates. The information obtained in this study can be used to design nanoscale heaters and actuators.

The thermo-optical properties of gold nanoparticles (NPs) embedded in an ice matrix were investigated using photoluminescence and Raman spectroscopy. An intense laser beam alone will not melt ice, but the addition of embedded Au NPs allows for melting with resonant laser light of relatively weak intensity. This is due to the strong absorption of Au NPs in the plasmon resonance regimen. We can determine the threshold melting power, P melting (T), where T is the background temperature by recording time-resolved Raman scattering signals of the system. A resultant loss of ice signal indicates melting and an absence of conversion to water implicates an irreversible loss of water molecules to the gas phase due to the location of the Au NP agglomerate at or near the ice/vapor surface. For fully embedded NP agglomerates, the ice/water phase transition can be monitored through Raman spectroscopy and the number of NPs in an agglomerate and their interactions can have a greater effect on localized heat generation. The local temperature inside and around the NP agglomerate depends strongly on its geometry and leads to a large scatter in the measured P melting as a function of the reduced temperature for different agglomerates. Immobilized Au NP agglomerates can also be characterized using single-particle spectroscopy, and results show that the plasmon emission of Au NPs scales with the number of NPs in an agglomerate.

This study set out to elucidate the growth of thin film water on a hydroxylated R-Al 2 O 3 (0001) surface using FTIR spectroscopy. The absorption of water on metal oxide surfaces, particularly aluminum oxides, alters the surface chemical reactivity and structure. We are able to detect an infrared signature due to surface bound water that is different than multilayer water. We use this infrared signature to separate and quantify the amount of water at the surface or interfacial water from the total amount of water adsorbed. Also, we use this information to model the growth of the interfacial water layer as compared to total water absorption and show that initially water does not wet the R-Al 2 O 3 (0001) surface completely. We are able to extract a small contact angle (1.9 × 10 -4 ) and spreading parameter (-4 × 10 -10 ) for thin-film water growth up to ∼7 monolayer equivalents and show that thin-film water grows as droplets that conserve contact angle.

Techniques for the prediction, measurement, and improvement of student performance were examined in an introductory physics course required for engineering majors. The contributions of this study include ͑1͒ the application of a statistical technique for predicting performance, ͑2͒ a computer program for training basic problem-solving skills, and ͑3͒ evidence for the value of training with complex homework problems. The prediction of performance was calculated using the method of discriminant analysis and data from the student's academic record. Specifically, this method predicted the chance of a satisfactory grade or a risk of failure using the student's grade point average ͑GPA͒ at entry to the course and grades in certain preceding technical courses. The technique was successful in predicting outcome of the course for over 70% of the students and provided a baseline of anticipated performance against which the results of an intervention could be measured. Improvement of performance resulted from two intervention techniques that modified the students' out-of-class assignments. The first intervention was Precision Teaching; a modification of homework exercises designed to improve basic skills in problem solving. Evaluation of this intervention indicated that class performance improved substantially; the number of students failing the course dropped to about one-half of that predicted by the discriminant analysis technique and overall class performance improved by almost one letter grade. The second intervention was based on the use of complex, multi-step homework problems designed to discourage ''matching'' of problems to operational formulae in the text. Evaluation of this intervention indicated that student performance on specific parts of the curriculum improved by 10%-20%. Both of these techniques resulted in significant improvement in performance largely on the final examinations.

This paper describes a first-year general chemistry laboratory that uses NMR spectroscopy and model building to emphasize molecular shape and structure. It is appropriate for either a traditional or an atoms-first curriculum. Students learn the basis of structure and the use of NMR data through a cooperative learning hands-on laboratory experience, and work in groups to assign names and structures to unknown compounds. This laboratory can be successfully run at a number of experimental levels, from students preparing their own NMR samples for analysis to running this as a dry laboratory with spectra provided by the instructor.