K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μ m of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μ m length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.
Characterizing and identifying cells in multicellular in vitro models remain a substantial challenge. Here, we utilize hyperspectral confocal Raman microscopy and principal component analysis coupled with linear discriminant analysis to form a label-free, noninvasive approach for classifying bone cells and osteosarcoma cells. Through the development of a library of hyperspectral Raman images of the K7M2-wt osteosarcoma cell lines, 7F2 osteoblast cell lines, RAW 264.7 macrophage cell line, and osteoclasts induced from RAW 264.7 macrophages, we built a linear discriminant model capable of correctly identifying each of these cell types. The model was cross-validated using a k-fold cross validation scheme. The results show a minimum of 72% accuracy in predicting cell type. We also utilize the model to reconstruct the spectra of K7M2 and 7F2 to determine whether osteosarcoma cancer cells and normal osteoblasts have any prominent differences that can be captured by Raman. We find that the main differences between these two cell types are the prominence of the β-sheet protein secondary structure in K7M2 versus the α-helix protein secondary structure in 7F2. Additionally, differences in the CH2 deformation Raman feature highlight that the membrane lipid structure is different between these cells, which may affect the overall signaling and functional contrasts. Overall, we show that hyperspectral confocal Raman microscopy can serve as an effective tool for label-free, nondestructive cellular classification and that the spectral reconstructions can be used to gain deeper insight into the differences that drive different functional outcomes of different cells.
Hoglund, Eric R.; Bao, De-Liang; O'Hara, Andrew; Makarem, Sara; Piontkowski, Zachary T.; Matson, Joseph R.; Yadav, Ajay K.; Haislmaier, Ryan C.; Ihlefeld, Jon F.; Ravichandran, Jayakanth; Ramesh, Ramamoorthy; Caldwell, Joshua D.; Beechem, Thomas E.; Tomko, John; Hachtel, Jordan A.; Pantelides, Sokrates T.; Hopkins, Patrick E.; Howe, James M.
As the length scales of materials decrease, the heterogeneities associated with interfaces become almost as important as the surrounding materials. This has led to extensive studies of emergent electronic and magnetic interface properties in superlattices. However, the interfacial vibrations that affect the phonon-mediated properties, such as thermal conductivity, are measured using macroscopic techniques that lack spatial resolution. Although it is accepted that intrinsic phonons change near boundaries, the physical mechanisms and length scales through which interfacial effects influence materials remain unclear. Here we demonstrate the localized vibrational response of interfaces in strontium titanate–calcium titanate superlattices by combining advanced scanning transmission electron microscopy imaging and spectroscopy, density functional theory calculations and ultrafast optical spectroscopy. Structurally diffuse interfaces that bridge the bounding materials are observed and this local structure creates phonon modes that determine the global response of the superlattice once the spacing of the interfaces approaches the phonon spatial extent. Our results provide direct visualization of the progression of the local atomic structure and interface vibrations as they come to determine the vibrational response of an entire superlattice. Direct observation of such local atomic and vibrational phenomena demonstrates that their spatial extent needs to be quantified to understand macroscopic behaviour. Tailoring interfaces, and knowing their local vibrational response, provides a means of pursuing designer solids with emergent infrared and thermal responses.
The interplay of stress, disorder, and Coulomb screening dictating the mobility of doped cadmium oxide (CdO) is examined using Raman spectroscopy to identify the mechanisms driving dopant incorporation and scattering within this emerging infrared optical material. Specifically, multi-wavelength Raman and UV-vis spectroscopies are combined with electrical Hall measurements on a series of yttrium (X = Y) and indium (X = In) doped X:CdO thin-films. Hall measurements confirm n-type doping and establish carrier concentrations and mobilities. Spectral fitting along the low-frequency Raman combination bands, especially the TA+TO(X) mode, reveals that the evolution of strain and disorder within the lattice as a function of dopant concentration is strongly correlated with mobility. Coupling between the electronic and lattice environments was examined through analysis of first- and second-order longitudinal-optical phonon-plasmon coupled modes that monotonically decrease in energy and asymmetrically broaden with increasing dopant concentration. By fitting these trends to an impurity-induced Fröhlich model for the Raman scattering intensity, exciton-phonon and exciton-impurity coupling factors are quantified. These coupling factors indicate a continual decrease in the amount of ionized impurity scattering with increasing dopant concentration and are not as well correlated with mobility. This shows that lattice strain and disorder are the primary determining factors for mobility in donor-doped CdO. In aggregate, the study confirms previously postulated defect equilibrium arguments for dopant incorporation in CdO while at the same time identifying paths for its further refinement.