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- Aminated surfaces (1)
- Chemical derivatization (1)
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Die Produktion von elektronischen, optischen und elektro-mechanischen Mikro- und Nanosystemen stellt hohe Anforderungen an die Messtechnik, um die Fertigungsprozesse zu optimieren und die Qualität zu prüfen. Existierende Messverfahren unterliegen Beschränkungen hinsichtlich des Auflösungsvermögens, der Messfeldgröße und des Ergebnisses der Messung. Der kombinierte Einsatz von Sensoren mit unterschiedlichen Fähigkeiten in den Auflösungsstufen mittels einer intelligenten Messstrategie ermöglicht eine effiziente Prüfung.
Neben den geeigneten Prüfstrategien werden auch Methoden zur Fusion und Auswertung der Daten von Sensoren mit unterschiedlichen Auflösungsfähigkeiten benötigt. Datenfusion bezeichnet dabei das Zusammenfügen verschiedener Messungen, um entweder unterschiedliche Eigenschaften eines Messobjekts in einem gemeinsamen Koordinatensystem angeben zu können oder um aus verschiedenen Messungen derselben Eigenschaft des Messobjekts einen Datensatz von höherer Qualität gegenüber den einzelnen Datensätzen zu erhalten. Voraussetzung für die Datenfusion ist Registrierung, die eine Überführung von Messdaten unterschiedlicher Messfelder oder Messmittel in ein gemeinsames Koordinatensystem darstellt und Thema dieses Beitrages ist.
Chemical derivatization XPS is used for the quantitative determination of amines at conventional organic surfaces, and it is also applied to plasma-processed aminated surfaces. When using TFBA and PFB as derivatization reagents for tagging primary amino groups, unexpected fluorine species were observed in the second case. The existence of reaction pathways other than those expected for amine derivatization with PFB or TFBA has to be assumed. This phenomenon is tentatively interpreted as the result of C—F bond cleavage during derivatization reactions of TFBA and PFB at plasma-polymerized allylamine and other plasma-processed aminated surfaces. As a consequence, quantification procedures based on derivatization by PFB or TFBA will underestimate amine surface concentrations.
Over the last 15 years significant advancements in induced polarization (IP) research have taken place, particularly with respect to spectral IP (SIP), concerning the understanding of the mechanisms of the IP phenomenon, the conduction of accurate and broadband laboratory measurements, the modelling and inversion of IP data for imaging purposes and the increasing application of the method in near-surface investigations. We summarize here the current state of the science of the SIP method for near-surface applications and describe which aspects still represent open issues and should be the focus of future research efforts. Significant progress has been made over the last decade in the understanding of the microscopic mechanisms of IP; however, integrated mechanistic models involving different possible polarization processes at the grain/pore scale are still lacking. A prerequisite for the advances in the mechanistic understanding of IP was the development of improved laboratory instrumentation, which has led to a continuously growing data base of SIP measurements on various soil and rock samples. We summarize the experience of numerous experimental studies by formulating key recommendations for reliable SIP laboratory measurements. To make use of the established theoretical and empirical relationships between SIP characteristics and target petrophysical properties at the field scale, sophisticated forward modelling and inversion algorithms are needed. Considerable progress has also been made in this field, in particular with the development of complex resistivity algorithms allowing the modelling and inversion of IP data in the frequency domain. The ultimate goal for the future are algorithms and codes for the integral inversion of 3D, time-lapse and multi-frequency IP data, which defines a 5D inversion problem involving the dimensions space (for imaging), time (for monitoring) and frequency (for spectroscopy). We also offer guidelines for reliable and accurate measurements of IP spectra, which are essential for improved understanding of IP mechanisms and their links to physical, chemical and biological properties of interest. We believe that the SIP method offers potential for subsurface structure and process characterization, in particular in hydrogeophysical and biogeophysical studies.