In der vorliegenden Arbeit werden die optischen Eigenschaften von dünnen PTCDA und TiOPc Schichten untersucht. Dies wurde mit der Kombination der Methoden der Molekularstrahlepitaxie (OMBE), der differentiellen Reflexionsspektroskopie (DRS) und Photolumineszenzmessungen möglich. Dabei steht der Übergang vom Einzelmolekül zum molekularen Festkörper im Mittelpunkt. Der realisierte optische Aufbau ermöglicht es, die optischen Eigenschaften von molekularen Sub- und Multilagen während der Schichtabscheidung im Ultrahochvakuum (UHV) zu bestimmen. Eine Strukturuntersuchung kann so unmittelbar darauf im UHV durchgeführt werden, ohne Umordnungsprozesse durch einen Probe-Luft-Kontakt zu riskieren. In dieser Arbeit wurden PTCDA-Schichten auf Muskovit-Glimmer(0001) und auf Au(100) untersucht. Auf Glimmer wird sehr gut ausgeprägtes Lagenwachstum gefunden, die Moleküle bilden auf dem schwach wechselwirkenden Substrat hochgeordnete epitaktische Filme. Dies ermöglichte für PTCDA, als quasi-eindimensionaler Molekülkristall, die optische Charakterisierung von Monomeren, Stapel-Dimeren und -Oligomeren während des Filmwachstums mittels DRS und Photolumineszenzmessungen. Die DRS-Messungen zeigen, daß die bekannten Festkörpereigenschaften schon bei Schichtdicken in der Größenordnung von 3-4 Gitterkonstanten ausgeprägt sind. Bis zu diesen Dicken sind die wesentlichen Änderungen in den optischen Eigenschaften zu beobachten. Ausgehend von Monomer-typischen Spektren entwickeln sich in dieser Dickenskale bereits alle Charakteristika der Festkörperspektren, wobei der Monomer-Dimerübergang die gravierendsten spektralen Änderungen hervorruft. Diese überraschende Tatsache war von den gängigen Theorien so nicht zu erwarten und ist Beleg für eine starke Wechselwirkung zwischen den dicht gepackten Molekülen. Steigen die Dimensionen des Films weiter, gibt es nur noch marginale Änderungen, die sich hauptsächlich in spektralen Verschiebungen äußern. Diese "finite-size" Effekte sind mit gängigen Theorien der Delokalisation der molekularen Anregung verträglich. Die Größe der Verschiebungen deutet jedoch darauf hin, daß gestalt- und dickenabhängige dielektrische Effekte gegenüber Delokalisierung und Confinement von Excitonen dominieren. Die veränderte Substratwechselwirkung auf der Au(100)-Oberfläche zeigt sich sowohl in verändertem Filmwachstum als auch abweichenden optischen Eigenschaften. Es wurde beobachtet, daß sich die Einflüsse durch die Substratbindung auf der Längenskala von nur einer Gitterkonstanten auswirken. Die PTCDA-Lagen, die auf dieser hybridisierten Grenzschichtlage wachsen, haben bereits die vom ungestörten System bekannten Eigenschaften. Da auf der Goldoberfläche mit zunehmender Schichtdicke das Inselwachstum (Stranski-Krastanov-Wachstum) überwiegt, verwischen die schichtabhängigen spektralen Änderungen zusehends. Für TiOPc auf Glimmer(0001) wurde bei Raumtemperatur amorphes Wachstum beobachtet, mit weniger gravierenden spektralen Änderungen. Jedoch sind auch in diesem System große dickenabhängige Verschiebungen in den Spektren festzustellen, die wie im Fall von PTCDA-Schichten hauptsächlich dielektrischen Effekten zugerechnet werden können. In TiOPc/PTCDA-Heteroschichten auf Glimmer konnte der Energietransfer vom PTCDA zum TiOPc auf molekularer Ebene, durch Löschung der PTCDA-Lumineszenz und anschließender sensibilisierter Emission des TiOPc, nachgewiesen werden. Dabei wurde bei sehr kleinen TiOPc-Schichtdicken die Emission von TiOPc-Monomeren beobachtet. Zusätzlich wurde eine dem Anion TiOPc- zuzurechnende Emission, als Indiz einer Ladungstrennung auf molekularer Ebene festgestellt. Bei größeren TiOPc-Schichtdicken tritt Exciplexemission auf, als Beleg für die starke Molekül-Molekül-Wechselwirkung an der Grenzfläche. Bei dickeren Schichten wird mit zunehmender Aggregation der TiOPc-Moleküle, die Lumineszenzausbeute durch Öffnung einer Reihe von nichtstrahlenden Rekombinationsmöglichkeiten, wie auch bei PTCDA beobachtet, geringer.

Speciale. / Haves kun i elektronisk udg.

From the Proceedings of the 1975 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 11-12, 1975, Tempe, Arizona / Space-age technology has produced tools which when turned to earthly pursuits can provide information on food and fiber production. Soil moisture has the potential for being remotely assessed, and three techniques for accomplishing this are under study. Two of the methods, reflectance and thermal, are sensitive to the conditions of the bare soil surface. The third technique, microwave emission, appears to have a good potential for assessing soil moisture with depth, because of its greater wavelength.

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The measurement of plant water content is essential to assess stress and disturbance in forest plantations. Traditional techniques to assess plant water content are costly, time consuming and spatially restrictive. Remote sensing techniques offer the alternative of a non destructive and instantaneous method of assessing plant water content over large spatial scales where ground measurements would be impossible on a regular basis. The aim of this research was to assess the relationship between plant water content and reflectance data in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa. Field reflectance and first derivative reflectance data were correlated with plant water content. The first derivative reflectance performed better than the field reflectance data in estimating plant water content with high correlations in the visible and mid-infrared portions of the electromagnetic spectrum. Several reflectance indices were also tested to evaluate their effectiveness in estimating plant water content and were compared to the red edge position. The red edge position calculated from the first derivative reflectance and from the linear four-point interpolation method performed better than all the water indices tested. It was therefore concluded that the red edge position can be used in association with other water indices as a stable spectral parameter to estimate plant water content on hyperspectral data. The South African satellite SumbandilaSat is due for launch in the near future and it is essential to test the utility of this satellite in estimating plant water content, a study which has not been done before. The field reflectance data from this study was resampled to the SumbandilaSat band settings and was put into a neural network to test its potential in estimating plant water content. The integrated approach involving neural networks and the resampled field spectral data successfully predicted plant water content with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 1.41 on an independent test dataset outperforming the traditional multiple regression method of estimation. The potential of the SumbandilaSat wavebands to estimate plant water content was tested using a sensitivity analysis. The results from the sensitivity analysis indicated that the xanthophyll, blue and near infrared wavebands are the three most important wavebands used by the neural network in estimating plant water content. It was therefore concluded that these three bands of the SumbandilaSat are essential for plant water estimation. In general this study showed the potential of up-scaling field spectral data to the SumbandilaSat, the second South African satellite scheduled for launch in the near future. / Thesis (M.Sc.) - University of KwaZulu-Natal, Pietermaritzburg, 2008.

To produce high quality paper, lignin should be removed from the pulp. Quantification of lignin concentrations using standard wet chemistry is accurate but time consuming and costly, thus not appropriate for a large number of samples. The ability of hyperspectral remote sensing to predict foliar lignin concentrations could be utilized to estimate wood lignin concentrations if meaningful relationships between wood and foliar chemistry are established. LAI (leaf area index) is a useful parameter that is incorporated into physiological models in forest assessment. Measuring LAI over vast areas is labour intensive and expensive; therefore, LAI has been correlated to vegetation indices using remote sensing. Broadband indices use average spectral information over broad bandwidths; therefore details on the characteristics of the forest canopy are compromised and averaged. Moreover, the broadband indices are known to be highly affected by soil background at low vegetation cover. The aim of this study is to determine foliar and wood lignin concentrations of Eucalyptus clones using hyperspectral lignin indices, and to estimate LAI of Eucalyptus clones from narrowband vegetation indices in Zululand, South Africa Twelve Eucalyptus compartments of ages between 6 and 9 years were selected and 5 trees were randomly sampled from each compartment. A Hyperion image was acquired within ten days of field sampling, SI and LAI measurements. Leaf samples were analyzed in the laboratory using the Klason method as per Tappi standards (Tappi, 1996-1997). Wood samples were analyzed for lignin concentrations using a NIRS (Near Infrared Spectroscopy) instrument. The results showed that there is no general model for predicting wood lignin concentrations from foliar lignin concentrations in Eucalyptus clones of ages between 6 and 9 years. Regression analysis performed for individual compartments and on compartments grouped according to age and SI showed that the relationship between wood and foliar lignin concentration is site and age specific. A Hyperion image was georeferenced and atmospherically corrected using ENVI FLAASH 4.2. The equation to calculate lignin indices for this study was: L1R= ~n5il: A'''''y . 1750 AI680 The relationship between the lignin index and laboratory-measured foliar lignin was significant with R2 = 0.79. This relationship was used to calculate imagepredicted foliar lignin concentrations. Firstly, the compartment specific equations were used to calculate predicted wood lignin concentrations from predicted foliar lignin concentrations. The relationship between the laboratorymeasured wood lignin concentrations and predicted wood lignin concentrations was significant with R2 = 0.91. Secondly, the age and site-specific equations were used to convert foliar lignin concentration to wood lignin concentrations. The wood lignin concentrations predicted from these equations were then compared to the laboratory-measured wood lignin concentrations using linear regression and the R2 was 0.79 with a p-value lower than 0.001. Two bands were used to calculate nine vegetation indices; one band from the near infrared (NIR) region and the other from the short wave infrared (SWIR). Correlations between the Vis and the LAI measurements were generated and . then evaluated to determine the most effective VI for estimating LAI of Eucalyptus plantations. All the results obtained were significant but the NU and MNU showed possible problems of saturation. The MNDVI*SR and SAVI*SR produced the most significant relationships with LAI with R2 values of 0.899 and 0.897 respectively. The standard error for both correlations was very low, at 0.080, and the p-value of 0.001. It was concluded that the Eucalyptus wood lignin concentrations can be predicted using hyperspectral remote sensing, hence wood and foliar lignin concentrations can be fairly accurately mapped across compartments. LAI significantly correlated to eight of the nine selected vegetation indices. Seven Vis are more suitable for LAI estimations in the Eucalyptus plantations in Zululand. The NU and MNU can only be used for LAI estimations in arid or semi-arid areas. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.

Pelchem, a commercial subsidiary of Necsa (South African Nuclear Energy Corporation), produces a range of commercial fluorocarbon products while driving research and development initiatives to support the fluorine product portfolio. One such initiative is to develop improved analytical techniques to analyse product composition during development and to quality assure produce. Generally the C–F type products produced by Necsa are in a solution of anhydrous HF, and cannot be directly analyzed with traditional techniques without derivatisation. A technique such as vibrational spectroscopy, that can analyze these products directly without further preparation, will have a distinct advantage. However, spectra of mixtures of similar compounds are complex and not suitable for traditional quantitative regression analysis. Multivariate data analysis (MVA) can be used in such instances to exploit the complex nature of spectra to extract quantitative information on the composition of mixtures. A selection of fluorocarbon alcohols was made to act as representatives for fluorocarbon compounds. Experimental design theory was used to create a calibration range of mixtures of these compounds. Raman and infrared (NIR and ATR–IR) spectroscopy were used to generate spectral data of the mixtures and this data was analyzed with MVA techniques by the construction of regression and prediction models. Selected samples from the mixture range were chosen to test the predictive ability of the models. Analysis and regression models (PCR, PLS2 and PLS1) gave good model fits (R2 values larger than 0.9). Raman spectroscopy was the most efficient technique and gave a high prediction accuracy (at 10% accepted standard deviation), provided the minimum mass of a component exceeded 16% of the total sample. The infrared techniques also performed well in terms of fit and prediction. The NIR spectra were subjected to signal saturation as a result of using long path length sample cells. This was shown to be the main reason for the loss in efficiency of this technique compared to Raman and ATR–IR spectroscopy. It was shown that multivariate data analysis of spectroscopic data of the selected fluorocarbon compounds could be used to quantitatively analyse mixtures with the possibility of further optimization of the method. The study was a representative study indicating that the combination of MVA and spectroscopy can be used successfully in the quantitative analysis of other fluorocarbon compound mixtures. / Thesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2012.

Pelchem, a commercial subsidiary of Necsa (South African Nuclear Energy Corporation), produces a range of commercial fluorocarbon products while driving research and development initiatives to support the fluorine product portfolio. One such initiative is to develop improved analytical techniques to analyse product composition during development and to quality assure produce. Generally the C–F type products produced by Necsa are in a solution of anhydrous HF, and cannot be directly analyzed with traditional techniques without derivatisation. A technique such as vibrational spectroscopy, that can analyze these products directly without further preparation, will have a distinct advantage. However, spectra of mixtures of similar compounds are complex and not suitable for traditional quantitative regression analysis. Multivariate data analysis (MVA) can be used in such instances to exploit the complex nature of spectra to extract quantitative information on the composition of mixtures. A selection of fluorocarbon alcohols was made to act as representatives for fluorocarbon compounds. Experimental design theory was used to create a calibration range of mixtures of these compounds. Raman and infrared (NIR and ATR–IR) spectroscopy were used to generate spectral data of the mixtures and this data was analyzed with MVA techniques by the construction of regression and prediction models. Selected samples from the mixture range were chosen to test the predictive ability of the models. Analysis and regression models (PCR, PLS2 and PLS1) gave good model fits (R2 values larger than 0.9). Raman spectroscopy was the most efficient technique and gave a high prediction accuracy (at 10% accepted standard deviation), provided the minimum mass of a component exceeded 16% of the total sample. The infrared techniques also performed well in terms of fit and prediction. The NIR spectra were subjected to signal saturation as a result of using long path length sample cells. This was shown to be the main reason for the loss in efficiency of this technique compared to Raman and ATR–IR spectroscopy. It was shown that multivariate data analysis of spectroscopic data of the selected fluorocarbon compounds could be used to quantitatively analyse mixtures with the possibility of further optimization of the method. The study was a representative study indicating that the combination of MVA and spectroscopy can be used successfully in the quantitative analysis of other fluorocarbon compound mixtures. / Thesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2012.

This paper deals with testing the method Reflectance Transformation Imaging (RTI) on the copy of the Piraeus-lion in Historic Museum in Stockholm. The purpose is to find out if it is possible to gather more information about the runic inscriptions. RTI is a method that records the surface normal of individual pixels in a digital photograph by analyzing the impact of light coming from different angles of entrance. RTI produces sort of a 3D-image of the object. There will be an overview of earlier interpretations of the runic scripts written on the lion as well as an overview of Varangians in the southeast. After examination of the lion with RTI, has a conclusion been made that the method should be performed again on similar items, and on the copy of the Piraeus-lion to evaluate its full potential.

Proportional loss models commonly used in disease surveys are based on the assumption that per cent yield loss is the same in all crops, regardless of their yield potential. Estimates of regional crop loss may be inaccurate if the relationship between disease and yield loss is affected by crop yield potential. The importance of crop yield potential in disease: yield loss modelling was investigated and models for more accurate regional crop loss estimates were developed, taking crop yield potential into account. Two spring sown barley (cv. Triumph) experiments were conducted in 1987/88 and 1988/89 in Canterbury, New Zealand, to study the effect of crop yield potential on the relationship between disease and yield loss. Crop yield potentials of 323 to 806gDM/m² were generated in seven crops by varying nitrogen and water inputs, sowing date (mid-spring and early-summer) and season. Leaf rust (Puccinia hordei Otth) epidemics of different severity were generated by applying fungicides at different times, frequencies and rates to control the natural epidemics. Disease was measured as per cent disease severity (%DS), green leaf area, radiation interception and near-infrared radiation (NIR) reflectance from crop canopies. Yield was measured as total and grain dry weight. Epidemics were severe in the fully diseased plots from GS 34 and 46 to maturity in the late and early sown crops respectively. Disease reduced grain yield by 50 to 63% in 1987/88 and 24 to 38% in 1988/89 in the fully diseased plots. Disease: yield loss models were derived by regression analysis for each crop in 1987/88. Single point, multiple point and area under curve models were derived from %DS and GLAI variables, and proportional (%) and actual (gDM/m²) grain yield. The effect of yield potential was determined by comparing regression equation coefficients for each crop with crop yield potential. An area under green leaf area index curve (AUGLAIC): actual yield model was best suited to determining the effect of yield potential on yield loss. This model was selected because AUGLAIC summarised the effect of disease on plant growth over the season and actual yield represented the crop yield potential in the absence of disease and the response of actual yield to disease. Crop yield potential did not affect actual yield loss caused by leaf rust. Disease measured as AUGLAIC explained most of the variation in yield (R²adj=0.93) for all crops in both years. Assessment of GLAI is not suitable for estimation of regional crop loss because of the requirement for a rapid and low cost method. Reflectance of NIR from the crop canopy was investigated as an alternative to GLAI measurements. Reflectance was correlated significantly (P<0.001) with GLAI (r=0.66 to 0.89) and green area index (r=0.76 to 0.92). Reflectance measured at grain-filling (GS 85-87) explained most (R²adj=0.94) of the variation in yield for all crops in both years. The relationship between AUGLAIC and yield was validated with data from independent diseased and healthy barley crops. The AUGLAIC: yield model described the effects of disease on yield accurately but overestimated yield by 49 to 108% in the healthy crops. Models based on accumulated PAR (photosynthetically active radiation) intercepted by green leaves explained the observed deviations in yield of these crops from the AUGLAIC: yield model. Accumulated PAR models accounted for differences in incident radiation, canopy structure, radiation interception by green leaves, radiation use efficiency and harvest index which are important in determining dry matter production and grain yield. Accumulated PAR models described the effects of disease on crop growth which were not represented by GLAI alone. Variation in crop yield potential at the regional scale is important in disease: yield loss modelling and can be accounted for by using either separate equations for each yield potential crop or crop category, robust models, inclusion of a form function for yield potential or choice of disease and yield variables which integrate yield potential.