Paderborn, Universiẗat, Diss., 1989. / Paderborn, Univ. Gesamthochsch., Diss., 1989.

Zugl.: Braunschweig, Techn. Univ., Diss., 2008

Das Felsenkellerlabor ist ein neues Untertagelabor im Bereich der nuklearen Astrophysik. Es befindet sich unter 47 m Hornblende-Monzonit Felsgestein im Stollensystem der ehemaligen Dresdner Felsenkellerbrauerei. Im Rahmen dieser Arbeit wird der Neutronenuntergrund in Stollen IV und VIII untersucht. Gewonnene Erkenntnisse aus Stollen IV hatten direkten Einfluss auf die geplanten Abschirmbedingungen fur Stollen VIII. Die Messung wurde mit dem Hensa-Neutronenspektrometer durchgeführt, welches aus polyethylenmoderierten 3He-Zählrohren besteht. Mit Hilfe des Monte-Carlo Programmes Fluka zur Simulation von Teilchentransport werden für das Spektrometer die Neutronen-Ansprechvermögen bestimmt. Fur jeden Messort wird außerdem eine Vorhersage des Neutronenflusses erstellt und die Labore hinsichtlich der beiden Hauptkomponenten aus myoneninduzierten Neutronen und Gesteinsneutronen aus (α,n)-Reaktionen und Spaltprozessen kartografiert. Die verwendeten Mess- und Analysemethoden finden in einer neuen Messung am tiefen Untertagelabor Lsc Canfranc Anwendung. Erstmalig werden im Rahmen dieser Arbeit vorläufige Ergebnisse vorgestellt. Des Weiteren werden Strahlenschutzsimulationen fur das Felsenkellerlabor präsentiert, welche den strahlenschutztechnischen Rahmen für die wissenschaftliche Nutzung definieren. Dabei werden die für den Sicherheitsbericht des Felsenkellers verwendeten Werte auf die Strahlenschutzverordnung 2018 aktualisiert. Letztlich werden Experimente an der Radiofrequenz-Ionenquelle am Felsenkeller vorgestellt, die im Rahmen dieser Arbeit technisch betreut wurde. Dabei werden Langzeitmessungen am übertägigen Teststand am Helmholtz-Zentrum Dresden-Rossendorf präsentiert.

This dissertation describes the improvement of signal analysis in ultrasonic microscopy for nondestructive testing. Specimens with many thin layers, like modern electronic components, pose a particular challenge for identifying and localizing defects. In this thesis, new evaluation algorithms have been developed which enable analysis of highly complex layer-stacks. This is achieved by a specific evaluation of multiple reflections, a newly developed iterative reconstruction and deconvolution algorithm, and the use of classification algorithms with a highly optimized simulation algorithm. Deep delaminations inside a 19-layer component can now not only be detected, but also localized. The new analysis methods also enable precise determination of elastic material parameters, sound velocities, thicknesses, and densities of multiple layers. The highly improved precision of determined reflections parameters with deconvolution also provides better and more conclusive results with common analysis methods. / Die vorgelegte Dissertation befasst sich mit der Verbesserung der Signalauswertung für die Ultraschallmikroskopie in der zerstörungsfreien Prüfung. Insbesondere bei Proben mit vielen dünnen Schichten, wie bei modernen Halbleiterbauelementen, ist das Auffinden und die Bestimmung der Lage von Fehlstellen eine große Herausforderung. In dieser Arbeit wurden neue Auswertealgorithmen entwickelt, die eine Analyse hochkomplexer Schichtabfolgen ermöglichen. Erreicht wird dies durch die gezielte Auswertung von Mehrfachreflexionen, einen neu entwickelten iterativen Rekonstruktions- und Entfaltungsalgorithmus und die Nutzung von Klassifikationsalgorithmen im Zusammenspiel mit einem hoch optimierten neu entwickelten Simulationsalgorithmus. Dadurch ist es erstmals möglich, tief liegende Delaminationen in einem 19-schichtigem Halbleiterbauelement nicht nur zu detektieren, sondern auch zu lokalisieren. Die neuen Analysemethoden ermöglichen des Weiteren eine genaue Bestimmung von elastischen Materialparametern, Schallgeschwindigkeiten, Dicken und Dichten mehrschichtiger Proben. Durch die stark verbesserte Genauigkeit der Reflexionsparameterbestimmung mittels Signalentfaltung lassen sich auch mit klassischen Analysemethoden deutlich bessere und aussagekräftigere Ergebnisse erzielen. Aus den Erkenntnissen dieser Dissertation wurde ein Ultraschall-Analyseprogramm entwickelt, das diese komplexen Funktionen auf einer gut bedienbaren Oberfläche bereitstellt und bereits praktisch genutzt wird.

This dissertation describes the improvement of signal analysis in ultrasonic microscopy for nondestructive testing. Specimens with many thin layers, like modern electronic components, pose a particular challenge for identifying and localizing defects. In this thesis, new evaluation algorithms have been developed which enable analysis of highly complex layer-stacks. This is achieved by a specific evaluation of multiple reflections, a newly developed iterative reconstruction and deconvolution algorithm, and the use of classification algorithms with a highly optimized simulation algorithm. Deep delaminations inside a 19-layer component can now not only be detected, but also localized. The new analysis methods also enable precise determination of elastic material parameters, sound velocities, thicknesses, and densities of multiple layers. The highly improved precision of determined reflections parameters with deconvolution also provides better and more conclusive results with common analysis methods.:Kurzfassung......................................................................................................................II Abstract.............................................................................................................................V List ob abbreviations........................................................................................................X 1 Introduction.......................................................................................................................1 1.1 Motivation.....................................................................................................................2 1.2 System theoretical description.....................................................................................3 1.3 Structure of the thesis..................................................................................................6 2 Sound field.........................................................................................................................8 2.1 Sound field measurement............................................................................................8 2.2 Sound field modeling..................................................................................................11 2.2.1 Reflection and transmission coefficients.........................................................11 2.2.2 Sound field modeling with plane waves..........................................................13 2.2.3 Generalized sound field position.....................................................................19 2.3 Receiving transducer signal.......................................................................................20 2.3.1 Calculation of the transducer signal from the sound field...............................20 2.3.2 Received signal amplitude..............................................................................21 2.3.3 Measurement of reference signals..................................................................24 3 Ultrasonic Simulation......................................................................................................27 3.1 State of the art............................................................................................................27 3.2 Simulation approach..................................................................................................28 3.2.1 Sound field measurement based simulation...................................................28 3.2.2 Reference signal based simulation.................................................................30 3.3 Determination of the impulse response.....................................................................31 3.3.1 1D ray-trace algorithm....................................................................................31 3.3.2 2D ray-trace algorithm....................................................................................33 3.3.3 Complexity reduction – optimizations.............................................................35 4 Deconvolution – Determination of reflection parameters............................................38 4.1 State of the art............................................................................................................39 4.1.1 Decomposition techniques..............................................................................39 4.1.2 Deconvolution.................................................................................................41 4.2 Analytic signal investigations for deconvolution.........................................................42 4.3 Single reference pulse deconvolution........................................................................44 4.4 Multi-pulse deconvolution..........................................................................................47 4.4.1 Homogeneous multi-pulse deconvolution.......................................................48 4.4.2 Multi-pulse deconvolution with simulated GSP profile....................................49 5 Reconstruction.................................................................................................................50 5.1 State of the art............................................................................................................50 5.2 Reconstruction approach...........................................................................................51 5.3 Direct material parameter estimation.........................................................................52 5.3.1 Sound velocities and layer thickness..............................................................52 5.3.2 Density, elastic modules and acoustic attenuation.........................................54 5.4 Iterative material parameter determination of a single layer......................................56 5.5 Reconstruction of complex specimens......................................................................60 5.5.1 Material characterization of multiple layers ....................................................60 5.5.2 Iterative simulation parameter optimization with correlation...........................62 5.5.3 Pattern recognition reconstruction of specimens with known base structure. 66 6 Applications and results.................................................................................................71 6.1 Analysis of stacked components................................................................................71 6.2 Time-of-flight and material analysis...........................................................................74 7 Conclusions and perspectives.......................................................................................78 References.......................................................................................................................82 Figures.............................................................................................................................86 Tables...............................................................................................................................88 Appendix..........................................................................................................................89 Acknowledgments.........................................................................................................100 Danksagung...................................................................................................................101 / Die vorgelegte Dissertation befasst sich mit der Verbesserung der Signalauswertung für die Ultraschallmikroskopie in der zerstörungsfreien Prüfung. Insbesondere bei Proben mit vielen dünnen Schichten, wie bei modernen Halbleiterbauelementen, ist das Auffinden und die Bestimmung der Lage von Fehlstellen eine große Herausforderung. In dieser Arbeit wurden neue Auswertealgorithmen entwickelt, die eine Analyse hochkomplexer Schichtabfolgen ermöglichen. Erreicht wird dies durch die gezielte Auswertung von Mehrfachreflexionen, einen neu entwickelten iterativen Rekonstruktions- und Entfaltungsalgorithmus und die Nutzung von Klassifikationsalgorithmen im Zusammenspiel mit einem hoch optimierten neu entwickelten Simulationsalgorithmus. Dadurch ist es erstmals möglich, tief liegende Delaminationen in einem 19-schichtigem Halbleiterbauelement nicht nur zu detektieren, sondern auch zu lokalisieren. Die neuen Analysemethoden ermöglichen des Weiteren eine genaue Bestimmung von elastischen Materialparametern, Schallgeschwindigkeiten, Dicken und Dichten mehrschichtiger Proben. Durch die stark verbesserte Genauigkeit der Reflexionsparameterbestimmung mittels Signalentfaltung lassen sich auch mit klassischen Analysemethoden deutlich bessere und aussagekräftigere Ergebnisse erzielen. Aus den Erkenntnissen dieser Dissertation wurde ein Ultraschall-Analyseprogramm entwickelt, das diese komplexen Funktionen auf einer gut bedienbaren Oberfläche bereitstellt und bereits praktisch genutzt wird.:Kurzfassung......................................................................................................................II Abstract.............................................................................................................................V List ob abbreviations........................................................................................................X 1 Introduction.......................................................................................................................1 1.1 Motivation.....................................................................................................................2 1.2 System theoretical description.....................................................................................3 1.3 Structure of the thesis..................................................................................................6 2 Sound field.........................................................................................................................8 2.1 Sound field measurement............................................................................................8 2.2 Sound field modeling..................................................................................................11 2.2.1 Reflection and transmission coefficients.........................................................11 2.2.2 Sound field modeling with plane waves..........................................................13 2.2.3 Generalized sound field position.....................................................................19 2.3 Receiving transducer signal.......................................................................................20 2.3.1 Calculation of the transducer signal from the sound field...............................20 2.3.2 Received signal amplitude..............................................................................21 2.3.3 Measurement of reference signals..................................................................24 3 Ultrasonic Simulation......................................................................................................27 3.1 State of the art............................................................................................................27 3.2 Simulation approach..................................................................................................28 3.2.1 Sound field measurement based simulation...................................................28 3.2.2 Reference signal based simulation.................................................................30 3.3 Determination of the impulse response.....................................................................31 3.3.1 1D ray-trace algorithm....................................................................................31 3.3.2 2D ray-trace algorithm....................................................................................33 3.3.3 Complexity reduction – optimizations.............................................................35 4 Deconvolution – Determination of reflection parameters............................................38 4.1 State of the art............................................................................................................39 4.1.1 Decomposition techniques..............................................................................39 4.1.2 Deconvolution.................................................................................................41 4.2 Analytic signal investigations for deconvolution.........................................................42 4.3 Single reference pulse deconvolution........................................................................44 4.4 Multi-pulse deconvolution..........................................................................................47 4.4.1 Homogeneous multi-pulse deconvolution.......................................................48 4.4.2 Multi-pulse deconvolution with simulated GSP profile....................................49 5 Reconstruction.................................................................................................................50 5.1 State of the art............................................................................................................50 5.2 Reconstruction approach...........................................................................................51 5.3 Direct material parameter estimation.........................................................................52 5.3.1 Sound velocities and layer thickness..............................................................52 5.3.2 Density, elastic modules and acoustic attenuation.........................................54 5.4 Iterative material parameter determination of a single layer......................................56 5.5 Reconstruction of complex specimens......................................................................60 5.5.1 Material characterization of multiple layers ....................................................60 5.5.2 Iterative simulation parameter optimization with correlation...........................62 5.5.3 Pattern recognition reconstruction of specimens with known base structure. 66 6 Applications and results.................................................................................................71 6.1 Analysis of stacked components................................................................................71 6.2 Time-of-flight and material analysis...........................................................................74 7 Conclusions and perspectives.......................................................................................78 References.......................................................................................................................82 Figures.............................................................................................................................86 Tables...............................................................................................................................88 Appendix..........................................................................................................................89 Acknowledgments.........................................................................................................100 Danksagung...................................................................................................................101

Heidelberg, Univ., Diss., 2007. / Online publiziert: 2008.

Stuttgart, Univ., Diss., 2003.

Single-molecule force spectroscopy (SMFS) with atomic force microscope (AFM) has advanced our knowledge of the mechanical aspects of biological processes, and helped us take big strides in the hitherto unexplored areas of protein (un)folding. One such virgin land is that of membrane proteins, where the advent of AFM has not only helped to visualize the difficult to crystallize membrane proteins at the single-molecule level, but also given a new perspective in the understanding of the interplay of molecular interactions involved in the construction of these molecules. My PhD work was tightly focused on exploiting this sensitive technique to decipher the intra- and intermolecular interactions in membrane proteins, using bacteriorhodopsin and bovine rhodopsin as model systems. Using single-molecule unfolding measurements on different bacteriorhodopsin oligomeric assemblies - trimeric, dimeric and monomeric - it was possible to elucidate the contribution of intra- and interhelical interactions in single bacteriorhodopsin molecules. Besides, intriguing insights were obtained into the organization of bacteriorhodopsin as trimers, as deduced from the unfolding pathways of the proteins from different assemblies. Though the unfolding pathways of bacteriorhodopsin from all the assemblies remained the same, the different occurrence probability of these pathways suggested a kinetic stabilization of bacteriorhodopsin from a trimer compared to that existing as a monomer. Unraveling the knot of a complex G-protein coupled receptor, rhodopsin, showed the existence of two structural states, a native, functional state, and a non-native, non-functional state, corresponding to the presence or absence of a highly conserved disulfide bridge, respectively. The molecular interactions in absence of the native disulfide bridge mapped onto the three-dimensional structure of native rhodopsin gave insights into the molecular origin of the neurodegenerative disease retinitis pigmentosa. This presents a novel technique to decipher molecular interactions of a different conformational state of the same molecule in the absence of a high-resolution X-ray crystal structure. Interestingly, the presence of ZnCl2 maintained the integrity of the disulfide bridge and the nature of unfolding intermediates. Moreover, the increased mechanical and thermodynamic stability of rhodopsin with bound zinc ions suggested a plausible role for the bivalent ion in rhodopsin dimerization and consequently signal transduction. Last but not the least, I decided to dig into the mysteries of the real mechanisms of mechanical unfolding with the help of well-chosen single point mutations in bacteriorhodopsin. The monumental work has helped me to solve some key questions regarding the nature of mechanical barriers that constitute the intermediates in the unfolding process. Of particular interest is the determination of altered occurrence probabilities of unfolding pathways in an energy landscape and their correlation to the intramolecular interactions with the help of bioinformatics tools. The kind of work presented here, in my opinion, will not only help us to understand the basic principles of membrane protein (un)folding, but also to manipulate and tune energy landscapes with the help of small molecules, proteins, or mutations, thus opening up new vistas in medicine and pharmacology. It is just a matter of a lot of hard work, some time, and a little bit of luck till we understand the key elements of membrane protein (un)folding and use it to our advantage.

Single-molecule force spectroscopy (SMFS) with atomic force microscope (AFM) has advanced our knowledge of the mechanical aspects of biological processes, and helped us take big strides in the hitherto unexplored areas of protein (un)folding. One such virgin land is that of membrane proteins, where the advent of AFM has not only helped to visualize the difficult to crystallize membrane proteins at the single-molecule level, but also given a new perspective in the understanding of the interplay of molecular interactions involved in the construction of these molecules. My PhD work was tightly focused on exploiting this sensitive technique to decipher the intra- and intermolecular interactions in membrane proteins, using bacteriorhodopsin and bovine rhodopsin as model systems. Using single-molecule unfolding measurements on different bacteriorhodopsin oligomeric assemblies - trimeric, dimeric and monomeric - it was possible to elucidate the contribution of intra- and interhelical interactions in single bacteriorhodopsin molecules. Besides, intriguing insights were obtained into the organization of bacteriorhodopsin as trimers, as deduced from the unfolding pathways of the proteins from different assemblies. Though the unfolding pathways of bacteriorhodopsin from all the assemblies remained the same, the different occurrence probability of these pathways suggested a kinetic stabilization of bacteriorhodopsin from a trimer compared to that existing as a monomer. Unraveling the knot of a complex G-protein coupled receptor, rhodopsin, showed the existence of two structural states, a native, functional state, and a non-native, non-functional state, corresponding to the presence or absence of a highly conserved disulfide bridge, respectively. The molecular interactions in absence of the native disulfide bridge mapped onto the three-dimensional structure of native rhodopsin gave insights into the molecular origin of the neurodegenerative disease retinitis pigmentosa. This presents a novel technique to decipher molecular interactions of a different conformational state of the same molecule in the absence of a high-resolution X-ray crystal structure. Interestingly, the presence of ZnCl2 maintained the integrity of the disulfide bridge and the nature of unfolding intermediates. Moreover, the increased mechanical and thermodynamic stability of rhodopsin with bound zinc ions suggested a plausible role for the bivalent ion in rhodopsin dimerization and consequently signal transduction. Last but not the least, I decided to dig into the mysteries of the real mechanisms of mechanical unfolding with the help of well-chosen single point mutations in bacteriorhodopsin. The monumental work has helped me to solve some key questions regarding the nature of mechanical barriers that constitute the intermediates in the unfolding process. Of particular interest is the determination of altered occurrence probabilities of unfolding pathways in an energy landscape and their correlation to the intramolecular interactions with the help of bioinformatics tools. The kind of work presented here, in my opinion, will not only help us to understand the basic principles of membrane protein (un)folding, but also to manipulate and tune energy landscapes with the help of small molecules, proteins, or mutations, thus opening up new vistas in medicine and pharmacology. It is just a matter of a lot of hard work, some time, and a little bit of luck till we understand the key elements of membrane protein (un)folding and use it to our advantage.

Die Arbeit befasst sich mit zweierleiZum einen wird der STM-Abbildungsprozess simuliert, indem Probe und Spitze durch zweidimensionale Sommerfeld-Metalle frei waehlbarer Geometrie beschrieben werden und der Tunnelstrom im Transfer-Hamiltonian-Formalismus bestimmt wird. Die Berechnung der Eigenzustaende der Elektroden erfolgt numerisch durch Diskretisierung der Schroedingergleichung im Differenzenverfahren. Ueber die geometrische Entfaltung der erhaltenen Konstantstromprofile mit der Spitzengeometrie werden der Vergleich zum geometrischen (mechanischen) Abtasten gezogen und Moeglichkeiten einer Vermessung von Spitze und Probe diskutiert. Zum anderen wird durch Berechnung von Eigenzustaenden in grossen zweidimensionalen Potentialkaesten (Quantenbillards) endlicher Wandhoehe der Frage nachgegangen, welchen Einfluss klassisch verbotene Gebiete (Aussenraum, Tunnelbarriere) auf Eigenfunktionen in semiklassisch grossen Systemen haben. Betrachtet wird insbesondere ein Gesamtsystem bestehend aus zwei Potentialkaesten, die ueber eine Tunnelbarriere koppeln (¨Quantenbillards endlicher Wandhoehe im Tunnelkontakt¨). Bei einer Reihe von Zustaenden zeigen sich Scars, die aus der Barriere austreten und in diese zuruecklaufen. Das Gesamtsystem ist in hohem Masse nichtintegrabel, ¨sichtbar¨ wird dieses aber nur fuer Bahnen entweder des Kontinuums oder fuer komplexe Orbits. Eine semiklassische Beschreibung dieses Phaenomens mit der gegenwaertigen, auf klassischen Orbits fussenden Theorie periodischer Bahnen ist nicht mehr moeglich. Die Einbeziehung komplexer Orbits oder Bahnen des Kontinuums (¨ungebundener Orbits¨) wird durch diese Ergebnisse angemahnt.