Search

Vocalizations of livestock convey information about the health and behavior of the animals, and vocal analysis could be a useful method to monitor livestock. We propose a deep learning classification of vocal recordings of laying hens and cattle with the aim of automatically classifying laying hen and cattle sounds in South Korea using a deep learning model. Audio and video recordings of laying hens and cattle were acquired. We classified laying hens’ sounds into eight classes and cattle sounds into nine classes. Classified audio files were used for the development of convolutional neural network (CNN) models. Two types of CNN structures, one based on 2D ConVnet and the other based on a 1D model with long short-term memory, were developed and tested for modeling to classify the vocalizations of laying hens and cattle. The classification model based on 2D ConVnet performed better with a satisfactory classification accuracy of 75.78% for laying hens and 91.02% for cattle. Based on the results for the developed CNN models, it is expected that real-time voice monitoring could be applicable for providing animal physiological information to growers.

In this study, the correlation between the specific growth rate of Phaeodactylum tricornutum and fucoxanthin (fucoxanthin) biosynthesis was investigated both in batch and in semi-continuous cultures. Fucoxanthin content from P. tricornutum biomass showed a positive correlation with specific growth rate during the normal culture period. The maximum yield of fucoxanthin (2.42 mg g−1 dry biomass) was observed at day 5, and the highest specific growth rate (1.91) was observed at day 4, both of which were during the exponential phase. Upon treatment with growth inhibitors (AZD-8055 or norflurazon) during the exponential phase, fucoxanthin content decreased with growth rate in a concentration-dependent manner. In a semi-continuous culture of P. tricornutum with dilution rates from 0.1 to 0.5 day−1, we found a positive correlation between specific growth rate and fucoxanthin biosynthesis in a steady-state condition. Based on the transcriptome analysis results, different metabolic and key regulatory genes were active at different growth phases. Particularly, during the exponential growth phase, various genes related to regulatory mechanisms, such as cell growth and replication, were expressed, whereas in the stationary phase, their expression was reduced. In the fucoxanthin biosynthesis pathway, 1-deoxy-d-erythritol 2,4-cyclodiphosphate synthase (ISPD) and violaxanthin deepoxidase (VDE) genes showed higher expression levels in the exponential phase, thus indicating that they are critical genes for the regulation of fucoxanthin biosynthesis in P. tricornutum. Our results are valuable to our understanding of the basic mechanism of fucoxanthin biosynthesis, thus providing theoretical guidance for the commercial production of fucoxanthin derived from P. tricornutum.

Gray mold disease is one of the most frequently occurring diseases in strawberries. Given that it spreads rapidly, rapid countermeasures are necessary through the development of early diagnosis technology. In this study, hyperspectral images of strawberry leaves that were inoculated with gray mold fungus to cause disease were taken; these images were classified into healthy and infected areas as seen by the naked eye. The areas where the infection spread after time elapsed were classified as the asymptomatic class. Square regions of interest (ROIs) with a dimensionality of 16 × 16 × 150 were acquired as training data, including infected, asymptomatic, and healthy areas. Then, 2D and 3D data were used in the development of a convolutional neural network (CNN) classification model. An effective wavelength analysis was performed before the development of the CNN model. Further, the classification model that was developed with 2D training data showed a classification accuracy of 0.74, while the model that used 3D data acquired an accuracy of 0.84; this indicated that the 3D data produced slightly better performance. When performing classification between healthy and asymptomatic areas for developing early diagnosis technology, the two CNN models showed a classification accuracy of 0.73 with regards to the asymptomatic ones. To increase accuracy in classifying asymptomatic areas, a model was developed by smoothing the spectrum data and expanding the first and second derivatives; the results showed that it was possible to increase the asymptomatic classification accuracy to 0.77 and reduce the misclassification of asymptomatic areas as healthy areas. Based on these results, it is concluded that the proposed 3D CNN classification model can be used as an early diagnosis sensor of gray mold diseases since it produces immediate on-site analysis results of hyperspectral images of leaves.

Background: The truss on tomato plants is a group or cluster of smaller stems where flowers and fruit develop, while a growing truss is the most extended part of the stem. Because the state of the growing truss reacts sensitively to the surrounding environment, it is essential to control the growth in the early stages. With the recent development of IT and artificial intelligence technology in agriculture, a previous study developed a real-time acquisition and evaluation method for images using robots. Further, we used image processing to locate the growing truss and flowering rooms to extract growth information such as the height of the flower room and hard crab. Among the different vision algorithms, the CycleGAN algorithm was used to generate and transform unpaired images using generatively learning images. In this study, we developed a robot-based system for simultaneously acquiring RGB and depth images of the tomato growing truss and flower room groups.Results: The segmentation performance for approximately 35 samples was compared through the false negative (FN) and false positive (FP) indicators. For the depth camera image, we obtained FN as 17.55±3.01% and FP as 17.76±3.55%. Similarly, for CycleGAN, we obtained FN as approximately 19.24±1.45% and FP as 18.24±1.54%. As a result of image processing through depth image, IoU was 63.56 ± 8.44%, and when segmentation was performed through CycelGAN, IoU was 69.25 ± 4.42%, indicating that CycleGAN is advantageous in extracting the desired growing truss. Conclusions: The scannability was confirmed when the image scanning robot drove in a straight line through the plantation in the tomato greenhouse, which confirmed the on-site possibility of the image extraction technique using CycleGAN. In the future, the proposed approach is expected to be used in vision technology to scan the tomato growth indicators in greenhouses using an unmanned robot platform.

We report high efficiency cell processing technologies for the ultra-thin Si solar cells based on crystalline Si thin foils (below a 50 µm thickness) produced by the proton implant exfoliation (PIE) technique. Shallow textures of submicrometer scale is essential for effective light trapping in crystalline Si thin foil based solar cells. In this study, we report the fabrication process of random Si nanohole arrays of ellipsoids by a facile way using low melting point metal nanoparticles of indium which were vacuum-deposited and dewetted spontaneously at room temperature. Combination of dry and wet etch processes with indium nanoparticles as etch masks enables the fabrication of random Si nanohole arrays of an ellipsoidal shape. The optimized etching processes led to effective light trapping nanostructures comparable to conventional micro-pyramids. We also developed the laser fired contact (LFC) process especially suitable for crystalline Si thin foil based PERC solar cells. The laser processing parameters were optimized to obtain a shallow LFC contact in conjunction with a low contact resistance. Lastly, we applied the random Si nanohole arrays and the LFC process to the crystalline Si thin foils (a 48 µm thickness) produced by the PIE technique and achieved the best efficiency of 17.1% while the planar PERC solar cell without the Si nanohole arrays exhibit 15.6%. Also, we demonstrate the ultra-thin wafer is bendable to have a 16 mm critical bending radius.

Maintaining environmental conditions for proper plant growth in greenhouses requires managing a variety of factors, ventilation is particularly important because inside temperatures can rise rapidly in warm climates. The structure of the window installed in a greenhouse is very diverse, and it is difficult to identify the characteristics that affect the temperature inside the greenhouse when multiple windows are driven, respectively. In this study, a new ventilation control logic using an output feedback neural-network (OFNN) prediction and optimization method was developed, and this approach was tested in multi-window greenhouses used for strawberry production. The developed prediction model used 15 inputs and achieved a highly accurate performance (R2 of 0.94). In addition, the method using an algorithm based on an OFNN was proposed for optimizing considered six window-opening behavior. Three case studies confirmed the optimization performance of OFNN in the nonlinear model and verified the performance through simulations. Finally, a control system based on this logic was used in a field experiment for six days by comparing two greenhouses driven by conventional control logic and the developed control logic, a comparison of the results showed RMSEs of 3.01 &deg, C and 2.45 &deg, C, respectively. It confirmed the improved control performance in comparison to a conventional ventilation control system.

Hydroponic plant culturing requires the concentration of nutrients in the supplied solution to be maintained at a constant level. For example, phosphate ion concentration directly affects crop growth, which necessitates the development of convenient and rapid techniques for on-site phosphate quantitation. Herein, we developed a new low-cost colorimetric method of quick on-site phosphate quantitation based on a modification of the conventional molybdenum colorimetric method. Specifically, the nutrient solution treated with ascorbic acid and molybdate was analyzed by colorimetric method after 10 min incubation, and a phosphate quantitation protocol was proposed. To verify this protocol, 50 nutrient solution samples with concentrations of 0–200 ppm were used to develop a model and perform a validation experiment, and the PLSR (Partial Least Squares Regression) and PCR (Principal Component Regression) models were developed and validated using a crossvalidation method and sample transmission spectra. The PLSR model, employing smoothing preprocessing at a 5 nm wavelength spacing, exhibited the best prediction performance and showed an error of ~10% within the measurement range during verification. In addition, an artificial neural network-based model achieved R2=0.93 for the training set and R2=0.86 for the validation set. Finally, we developed convenient-to-use software for phosphate ion quantitation by the presented method and performed a demonstration test.

We demonstrated fabrication of a parabola shaped Si nanostructures of various periods by combined approach of nanosphere lithography and a single step CF4/O2 reactive ion etch (RIE) process. Silica nanosphere monolayers in a hexagonal array were well deposited by a solvent controlled spin coating technique based on binary organic solvents. We showed numerically that a parabolic Si nanostructure of an optimal period among various-shaped nanostructures overcoated with a dielectric layer of a 70 nm thickness provide the most effective antireflection. As the simulation results as a design guide, we fabricated the parabolic Si nanostructures of a 520 nm period and a 300 nm height exhibiting the lowest weighted reflectance of 2.75%. With incorporation of such parabolic Si nanostructures, a damage removal process for 20 sec and SiNx antireflection coating of a 70 nm thickness, the efficiency of solar cells increased to 17.2% while that of the planar cells without the nanostructures exhibited 16.2%. The efficiency enhancement of the cell with the Si nanostructures was attributed to the improved photocurrents arising from the broad spectral antireflection which was confirmed by the external quantum efficiency (EQE) measurements.

The production of low potassium vegetables arose out of the dietary needs of patients with renal dysfunction. Attempts have been made to reduce potassium content in vegetables and fruits; however, induced potassium deficiency has often resulted in decreased yields. Here, we investigated a new method of producing low potassium kale and present the characteristics of the resulting produce. By substituting potassium nitrate with calcium nitrate in the nutrient solution 2 weeks before harvesting, the potassium content of kale was reduced by 70% without a deterioration in yield and semblance qualities. Despite no relationships being detected between potassium deficiency and anti-oxidative properties, the total glucosinolate content, an indicator of the anti-cancer effect of cruciferous vegetables, was significantly increased by potassium deficiency in kale. This study demonstrates a novel method of producing low potassium kale for patients with renal failure, without a reduction in yield but with beneficial increase in glucosinolates.

Simple Summary In the application of artificial intelligence and advanced sound technologies in animal sound classification, certain challenges are still faced, such as the disruptions of background noise. To address this problem, we propose a web-based and real-time cattle monitoring system for evaluating cattle conditions. The system contained a convolutional neural network (CNN) for classifying cattle vocals and removing background noise as well as another CNN for behavior classification from existing datasets. The developed model was applied to cattle sound data obtained from an on-site monitoring system through sensors and achieved a final accuracy of 81.96% after the sound filtering. Finally, the model was deployed on a web platform to assist farm owners in monitoring the conditions of their livestock. We believe that our study makes a significant contribution to the literature because it is the first attempt to combine CNN and Mel-frequency cepstral coefficients (MFCCs) for real-time cattle sound detection and a corresponding behavior matching. Abstract The priority placed on animal welfare in the meat industry is increasing the importance of understanding livestock behavior. In this study, we developed a web-based monitoring and recording system based on artificial intelligence analysis for the classification of cattle sounds. The deep learning classification model of the system is a convolutional neural network (CNN) model that takes voice information converted to Mel-frequency cepstral coefficients (MFCCs) as input. The CNN model first achieved an accuracy of 91.38% in recognizing cattle sounds. Further, short-time Fourier transform-based noise filtering was applied to remove background noise, improving the classification model accuracy to 94.18%. Categorized cattle voices were then classified into four classes, and a total of 897 classification records were acquired for the classification model development. A final accuracy of 81.96% was obtained for the model. Our proposed web-based platform that provides information obtained from a total of 12 sound sensors provides cattle vocalization monitoring in real time, enabling farm owners to determine the status of their cattle.

The dried Ganoderma lucidum (GL) has been widely used for its pharmacological properties and bioactive ganoderic acids (GAs). Herein, extraction procedures combining ultra-sonication and heating were optimized using response surface methodology based on four variables (antioxidant activity, anti-diabetic activity, total GAs content, and total polysaccharide content) and principal component analysis. The extraction of freeze-dried GL at temperatures between 64.2 and 70 °C for 1.2 h maximized the antioxidant activity and GA content, whereas the polysaccharide content and anti-diabetic activity were maximized by extraction between 66.8 and 70 °C for more than 2.8 h. Heat-dried GL extracted at 50 °C for 3 h provided the greatest anti-inflammatory activity against HaCaT cells by suppressing the response to inflammation related cytokines at mRNA levels. These results suggest that extraction conditions might be a limiting factor for target-oriented investigations, and optimized extraction methods may improve the potential effect and quality of harvested GL products.

This work was financially supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) (Grant No. 20143030011850), and funded by the Ministry of Trade, Industry and Energy (MOTIE). I. Kim acknowledges KUUC (KIST-UNIST-Ulsan Center for Convergent Materials) for partial financial support.

Texturing of silicon wafers with periodic gratings in submicron scale is one of effective light trapping routes especially for thin crystalline silicon solar cells. The grating can be very effective for trapping of photons near band gap of crystalline silicon when its period is suitably chosen. The asymmetric gratings provide higher light trapping efficiency than symmetric ones because the asymmetric one suppress the escape of internally reflected light in the silicon wafers. In this study, we conceptually show that asymmetric grating can be fabricated by simple stacking of a dielectric layer onto the symmetric silicon grating structures. Optical simulations were performed to calculate optical absorptions in thin crystalline silicon of a 5 μm thickness with symmetric and asymmetric grating structures. We demonstrate that with the asymmetric grating structures combined with highly efficient antireflection coating, optical absorptions in the thin silicon wafers can reach over 97% of the Lambertian absorption limit.

Ginseng is a perennial herb used as valuable traditional medicine for more than three thousand years. Ginsenosides are the major group of pharmacologically active components of ginseng, and they are effective against various diseases. Present study was designed to investigate the impact of foliar silicon sprays on growth characteristics, physiological traits, and pharmaceutical quality of 6-year-old ginseng plants. Three different concentrations i.e. 50 mg/L, 100 mg/L, and 200 mg/L of Si was used as foliar treatment. Compared to control, stem hardness was enhanced up to 54% in 100 mg/L treatment followed by 38% in 50 mg/L and 36% in 200 mg/L. SEM analysis showed that the density of epidermal cells was 21-25% higher in Si-treated plants than that in the control plants. Cuticle thickness was found higher in Si treated plants as compared to control. Overall a total of 25%, 38%, and 54% of cuticle thickness and 43%, 49%, and 63% ginseng roots production was observed in plants treated with Si treatment of 50 mg/L, 100 mg/L, and 200 mg/L, respectively. Results suggest that out of three different concentrations of Si treatments, 200 mg/L found to be most effective in overall higher Si content in leaves with thick cuticle and higher root production, 100 mg/L treatment showed high photosynthesis rate followed by stomatal conductance, chlorophyll content and stem hardness. 50 mg/L was found to be least effective. Out of 12 ginsenosides analyzed in 6-year-old ginseng roots, the most common were AP, Rg1, Rb1, and Re. The content of ginsenosides per gram of ginseng roots did not show any significant differences among treatments, but overall, ginsenosides contents were higher in Si-treated plants because of increased root growth triggered by increased Si level. Our study show that the application of aerial sprays with elevated Si levels increases the growth, promotes the physiological and morphological traits and increases the yield of 6-year-old ginseng plants. In addition, this study implied the importance of Si for commercial production of high-quality ginseng roots.

We propose an efficient and accurate finite-difference time-domain (FDTD) algorithm to simulate the absorbance of a thin-film solar cell containing nanometer particles or nonflat layers. This algorithm can extract a closed boundary for an arbitrarily shaped object, with the solar cell model being discretized into a set of Yee's cells to construct the FDTD system. Using this information, we can distinguish the closed boundaries of the components (e.g., particles or layers) of the solar cell and accurately calculate the absorbance of each particle or layer. Moreover, using the closed line (in 3-D, surface) integration instead of the area (in 3-D, volume) integration enables faster calculation and requires less memory.

Incorporation of noble metal nanoparticles such as Ag and Au in organic solar cells is one of the promising schemes for plasmonic absorption enhancements. The size of the metal nanoparticles in correlation with optical properties of organic semiconductors is one of crucial parameters for plasmonic enhancements. We analyzed the light scattering and absorption of Ag nanoparticles embedded in an absorbing media using the Mie theory. The size of Ag nanoparticles and the complex refractive index of the absorbing media were adjusted for the light scattering calculations, which reveal that the plasmonic absorption enhancements in the strongly absorbing medium are weakly dependent on the size of Ag nanoparticles and rather sensitive to their volume fractions.

We demonstrate the power conversion efficiency of bulk heterojunction organic solar cells can be enhanced by introducing Ag nanoparticles into organic exciton blocking layer. The Ag nanoparticles were incorporated into the exciton blocking layer by thermal evaporation. Compared with the conventional cathode contact materials such as Al, LiF/Al, devices with Ag nanoparticles incorporated in the exciton blocking layer showed lower series resistances and higher fill factors, leading to a 3.2% power conversion efficiency with a 60 nm active layer; whereas, the conventional devices have only 2.0–2.3% power conversion efficiency. Localized surface plasmon resonances by the Ag nanoparticles and their contribution to photocurrent were also discussed by simulating optical absorptions using a FDTD (finite-difference-time-domain) method.

Micro-dimples on sliding surfaces have been investigated to reduce the frictional forces on metal bearing surfaces; however, for an elastomer, such as thermoplastic polyurethane (TPU), this has not been studied. The material properties of an elastomer are affected by temperature, and this can shorten the life of the elastomer. In this paper, micro-dimples were applied on the surface of an elastomer in order to reduce the frictional heating, which was experimentally investigated using pin-on-disk apparatus while the surface temperature was measured. To obtain optimal design parameters, the design of the experiment was applied, and the shape of the section, size, depth and density of micro-dimples were selected as the design parameters. The results show that the size of the dimple is the most important design parameter.

The optical absorption efficiency (OAE) of thin crystalline Si (c-Si) solar cells was examined by using a direct absorption calculation algorithm based on the three-dimensional modeling and ray-tracing technique. The back contact was assumed to be made of ZnO based oxide layers with different optical constants and metallic electrode, and the front surface was assumed to be Lambertian. Simulation results showed that the insertion of non-absorptive oxide layer between c-Si and Al improved OAE, and that the relative amount of enhancement increased with decreasing refractive index, manifesting the reduction in absorption loss in Al electrode due to the increased total internal reflection. In the case of absorptive oxide layer, although increase in OAE was still attainable when compared with the back contact without oxide, the OAE was subdued significantly due to large absorption loss in oxide layer. The optimal oxide layer thickness was around 200 nm for non-absorptive oxide, and that of absorptive oxide decreased with increasing extinction coefficient. In the case of Ag metal contact, the enhancement of OAE due to the use of oxide layer was much less than the case of Al because of inherent high reflectivity and low absorption loss in Ag layer.

Optical properties, surface plasmon resonance (SPR) response characteristics, and the adhesion properties of the plasmonic stacks with titanium nitride (TiNx) adhesion layers were analyzed and compared with those of the Au single stack and the plasmonic stacks with conventional titanium adhesion layer. All the films were deposited by radio frequency magnetron sputtering. TiNx single layer exhibited higher electrical conductivity and reflectance in long wavelength range than Ti single layer of similar thickness. When compared with the plasmonic stacks with Ti adhesion layer, the plasmonic stacks with TiNx adhesion layer showed higher peak transmittance and less absorption loss in wavelength range longer than 500 nm. Examination of the SPR response curves revealed that much improved SPR characteristics could be attained if conventional Ti adhesion layer were replaced by TiNx layer, and it was attributed to the lower damping of TiNx film than Ti film at corresponding thickness. Also, it was proved that TiNx layer could provide sufficient adhesion strength at the glass/TiNx and TiNx/Au interfaces, which is comparable with that of Ti layer.

The demand to reduce Si usage in Si photovoltaic cells in order to improve the cost-effectiveness is ever-increasing in photovoltaic industry. In this study, we propose a new Si photovoltaic cell structure, in which Si grids are formed and reflectors are positioned in between. The optical absorption efficiency of the proposed cell structure was analyzed by making comparisons with simple Si cells with flat and textured surfaces. A quantitative analysis of the optical absorption was made by using a direct absorption calculation algorithm based on the three-dimensional modeling and ray-tracing technique. The proposed grid-type cell structure was shown to be able to yield an improvement in the absorption efficiency per unit Si volume as high as 91% when compared to typical Si cells with pyramidal surface texturing.

The microstructures of molybdenum (Mo) thin films deposited at pressures from 3.3 to 10.3 mTorr were characterized, and the relationships between these microstructures and the properties of the films (residual stress and electrical resistivity) were investigated. In the low deposition pressure regime (region I, below 7 m Torr), the residual stress in the tensile direction increases with increasing pressure and the electrical resistivity increases gradually, but at high deposition pressures (region II, above 7 m Torr) the residual stress is reduced and the resistivity increases more steeply. These variations of the properties of the Mo films in the low pressure regime are due to the variation in grain size; the carrier mobility decreases due to increased grain boundary (GB) scattering and the tensile stress increases due to increased atomic attraction across the GBs. In contrast, the porosity of the Mo films increases significantly in the high pressure regime, as demonstrated with variable angle spectroscopic ellipsometry (VASE). Most of these pores are believed to be present along the grain boundaries of the Mo films, so their presence reduces the GB attraction and thus the tensile stress and enhances the carrier scattering. The high porosity of the Mo back contact was shown with secondary ion mass spectroscopy profiling to accelerate the Na diffusion from soda-lime glass into the Cu(In,Ga)Se 2 (CIGS) film.

Solar cells, especially thin film solar cells, utilize rough surfaces actively in order to improve light trapping efficiency. In this study, we propose a new optical simulation method, which is capable of taking into consideration the realistic surface and interface morphology. The proposed simulation algorithm is based upon a non-sequential ray tracing technique, and direct calculation of the optical absorption energy is performed by separating the light passing through medium into the coherent part and the incoherent part in the course of non-sequential ray tracing throughout the whole region of solar cell structure. It was shown that the new method can give more accurate estimation of the absolute absorption energy in the individual layer when applied for a thin film Si solar cell structure with rough surface of bidirectional scattering distribution function. Furthermore, the proposed algorithm was proved to be very effective in analyzing solar cells with complex geometry like concentrator photovoltaic system, which necessitates the combination of coherent and incoherent calculation.

In this study, we present and demonstrate a new route to a great enhancement in resolution of surface plasmon resonance sensors. Basically, our approach combines a waveguide coupled plasmonic mode and a kind of Au/Ag bimetallic enhancement concept. Theoretical modeling was carried out by solving Fresnel equations for the multilayer stack of prism/Ag inner-metal layer/dielectric waveguide/Au outer-metal layer. The inner Ag layer couples incident light to a guided wave and makes more fields effectively concentrated on the outer Au surface. A substantial enhancement in resolution was experimentally verified for the model stack using a ZnS-SiO2 waveguide layer.

Al doped ZnO (AZO) films were prepared by radio frequency (rf) magnetron sputtering with varying substrate temperature, working Ar gas pressure and rf power imposed on 2-inch ZnO–Al 2 O 3 (2 wt%) target, and their electrical and structural properties together with the corresponding etching behavior in 0.5% HCl solution were examined. The effect of rf power on the electrical and structural properties of AZO films was marginal, but in the case of working Ar gas pressure and substrate temperature, substantial variations in the electrical and structural properties were observed. The optimum electrical properties were obtained for AZO film deposited at 150 °C in lowest working pressure of 1.2 mTorr. The behavior of crater formation upon etching varied significantly depending on the structure of the film, and it was shown that the etching rate could be expressed in inversely proportional function of the crystallinity represented as (002) peak intensity. Also, for films with similar crystallinity, i.e. (002) peak intensity, dense structured film deposited at high temperature had much lower etching rate than open structured films deposited under high working Ar gas pressure.

Al-doped ZnO (AZO) films prepared at different substrate temperature and AZO films with intentional Zn addition (ZAZO) during deposition at elevated substrate temperature were fabricated by radio frequency magnetron sputtering on glass substrate, and the resulting structural, electrical, optical properties together with the etching characteristics and annealing behavior were comparatively examined. AZO films deposited at 150 °C showed the optimum electrical properties and the largest grain size. XPS analysis revealed that AZO films deposited at elevated temperature of 450 °C contained large amount of Al content due to Zn deficiency, and that intentional Zn addition during deposition could compensate the deficiency of Zn to some extent. It was shown that the electrical, optical and structural properties of ZAZO films were almost comparable to those of AZO film deposited at 150 °C, and that ZAZO films had much smaller etching rate together with better stability in severe annealing conditions than AZO films due possibly to formation of dense structure.

Quantitative analysis of optical scattering intensities from a Au nanoparticle with a diameter of 100 nm, which is effected by the localized surface plasmon resonance (LSPR), were numerically carried out by using a dark-field detection scheme on prism basal plane for two different beam incident modes of reflectance (R-mode) and transmittance (T-mode). Two-dimensional finite difference time domain (FDTD) algorithm was adopted, and its applicabilibility was verified by comparing the simulation results with the theoretical ones. Simulation results of the scattered light intensities from a Au nanoparticle revealed that the scattered intensity of the T-mode was much stronger than that of R-mode. Comparison of the calculated results with the theoretical intensity distribution on the prism showed that the scattered intensity is marimized when the evanescent field, which is generated from the interface of prism and air at TIR angle, is coupled with Au nanoparticle.

Fluorine doped ZnO (FZO) films were deposited on Corning glass by radio frequency (rf) magnetron sputtering of pure ZnO target in CF 4 containing gas mixtures, and the compositional, electrical, optical, and structural properties of the as-grown films as well as the vacuum-annealed films were investigated. The fluorine content in FZO films increased with increasing CF 4 content in sputter gas. FZO films deposited at elevated temperature of 150 °C had considerably lower fluorine content and showed a poorer electrical properties than the films deposited at room temperature. Despite high fluorine contents in the films, for all the FZO films, the carrier concentration remained below 2×10 20 cm −3 , leading to fairly low doping efficiency level. Vacuum-annealing of the FZO films deposited at room temperature resulted in substantial increase of Hall mobilities, reaching as high as 43 cm 2 /Vs. This was attributed partly to the removing of oxygen vacancies and/or the forming chemical bonds with interstitial zinc atoms by fluorine interstitials and partly to the passivation effect of excess fluorine atoms by filling in the dangling bonds at the grain boundaries. For all the films with thickness of around 300 nm, the optical transmissions in visible were higher than 80%, and increased with increasing fluorine content up to 85% for the film with highest fluorine content.

In this study, we present theoretical and experimental analyses on the waveguide mode properties of prism-coupled Au:SiO2 nanocomposite films with the near infrared laser of 1550 nm wavelength where the optical absorption diminished enough for the generation of guided mode. The evolution of guided mode in the nanocomposite waveguide and its propagation properties were also evaluated. As an effective way of utilizing the surface plasmon resonance properties for the application to optical switching devices, we employed an attenuated total internal reflection type optical switch geometry and tested its effectiveness for the absorptive opto-functional materials system using a cross-modulation technique with 532-nm pump and 1550-nm probe beams. The index change probe beam experiences was found to be purely refractive in nature and negative in sign, presumably due to the photo-thermal effect induced in the nanocomposite film by the irradiation of pump beam.