strahlung christian korrektur

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diff --git a/Doering-PHD-Thesis/PHDthesis.out b/Doering-PHD-Thesis/PHDthesis.out
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diff --git a/Doering-PHD-Thesis/PHDthesis.toc b/Doering-PHD-Thesis/PHDthesis.toc
index c852d559f16e695568e6f7a9ac4aa501fc000ae8..4c6ca4884ed8c56c8bc91932c3ae9d34edf9fa36 100755 (executable)
--- a/Doering-PHD-Thesis/PHDthesis.toc
+++ b/Doering-PHD-Thesis/PHDthesis.toc
@@ -33,7 +33,7 @@
 \contentsline {subsection}{\numberline {3.3.2}Volumensch\"aden}{41}{subsection.3.3.2}
 \contentsline {subsection}{\numberline {3.3.3}Wechselwirkung}{43}{subsection.3.3.3}
 \contentsline {subsection}{\numberline {3.3.4}Random Telegraph Signal}{43}{subsection.3.3.4}
-\contentsline {chapter}{\numberline {4}Methoden zur Strahlenh\"arteuntersuchung 21.~Oktober 2013}{45}{chapter.4}
+\contentsline {chapter}{\numberline {4}Methoden zur Strahlenh\"arteuntersuchung 1.~November 2013}{45}{chapter.4}
 \contentsline {section}{\numberline {4.1}Experimenteller Aufbau}{45}{section.4.1}
 \contentsline {subsection}{\numberline {4.1.1}USB-System}{45}{subsection.4.1.1}
 \contentsline {subsection}{\numberline {4.1.2}PXI-System}{46}{subsection.4.1.2}
@@ -49,10 +49,10 @@
 \contentsline {subsection}{\numberline {4.2.4}Konzept Schwelle}{62}{subsection.4.2.4}
 \contentsline {subsection}{\numberline {4.2.5}Fixed Pattern Noise}{63}{subsection.4.2.5}
 \contentsline {subsection}{\numberline {4.2.6}Fehltreffer}{63}{subsection.4.2.6}
-\contentsline {subsection}{\numberline {4.2.7}Cluster}{65}{subsection.4.2.7}
+\contentsline {subsection}{\numberline {4.2.7}Cluster}{63}{subsection.4.2.7}
 \contentsline {subsection}{\numberline {4.2.8}Ladungsspektrum}{65}{subsection.4.2.8}
 \contentsline {subsubsection}{\numberline {4.2.8.1}Photon-Quelle}{65}{subsubsection.4.2.8.1}
-\contentsline {paragraph}{\numberline {4.2.8.1.1}Vetotrigger auf das Seedpixel}{69}{figure.caption.47}
+\contentsline {paragraph}{\numberline {4.2.8.1.1}Vetotrigger auf das Seedpixel}{68}{figure.caption.47}
 \contentsline {paragraph}{\numberline {4.2.8.1.2}Trigger auf Gesamtcluster}{69}{figure.caption.48}
 \contentsline {paragraph}{\numberline {4.2.8.1.3}Fe-55-Quelle}{70}{paragraph.4.2.8.1.3}
 \contentsline {paragraph}{\numberline {4.2.8.1.4}Cd-109-Quelle}{70}{paragraph.4.2.8.1.4}
@@ -72,9 +72,9 @@
 \contentsline {section}{\numberline {4.4}Einfluss parasit\"arer Oberfl\"achensch\"aden in mit Reaktorneutronen bestrahlten Sensoren}{82}{section.4.4}
 \contentsline {subsection}{\numberline {4.4.1}Vergleich mit Co-60-bestrahlten Sensoren}{85}{subsection.4.4.1}
 \contentsline {subsection}{\numberline {4.4.2}Ausheilverhalten}{86}{subsection.4.4.2}
-\contentsline {subsection}{\numberline {4.4.3}Zusammenfassung}{87}{subsection.4.4.3}
+\contentsline {subsection}{\numberline {4.4.3}Zusammenfassung}{86}{subsection.4.4.3}
 \contentsline {section}{\numberline {4.5}Zusammenfassung}{87}{section.4.5}
-\contentsline {chapter}{\numberline {5}Hochohmige CMOS-Sensoren 21.~Oktober 2013}{88}{chapter.5}
+\contentsline {chapter}{\numberline {5}Hochohmige CMOS-Sensoren 1.~November 2013}{88}{chapter.5}
 \contentsline {section}{\numberline {5.1}MAPS mit hochohmiger Epitaxieschicht}{88}{section.5.1}
 \contentsline {subsection}{\numberline {5.1.1}Ladungssammlungseffizienz des Seedpixels}{92}{subsection.5.1.1}
 \contentsline {subsubsection}{\numberline {5.1.1.1}MIMOSA-26-Puzzle}{94}{subsubsection.5.1.1.1}
@@ -107,7 +107,7 @@
 \contentsline {subsection}{\numberline {5.3.5}Zusammenfassung}{133}{subsection.5.3.5}
 \contentsline {section}{\numberline {5.4}Zusammenfassung}{134}{section.5.4}
 \contentsline {section}{\numberline {5.5}Schlussfolgerung}{134}{section.5.5}
-\contentsline {chapter}{\numberline {6}CMOS sensors im 0.18mu Prozess 21.~Oktober 2013}{135}{chapter.6}
+\contentsline {chapter}{\numberline {6}CMOS sensors im 0.18mu Prozess 1.~November 2013}{135}{chapter.6}
 \contentsline {section}{\numberline {6.1}Einf\"uhrung}{135}{section.6.1}
 \contentsline {section}{\numberline {6.2}Rauschverhalten}{136}{section.6.2}
 \contentsline {section}{\numberline {6.3}Ionisierende Strahlenh\"arte}{142}{section.6.3}

diff --git a/Doering-PHD-Thesis/Strahlung.aux b/Doering-PHD-Thesis/Strahlung.aux
index 30f783f6a4816177b2db29a9fefed6921e3b1106..f8cbf244919bf3d047149209d23a20f8387ed9c5 100755 (executable)
--- a/Doering-PHD-Thesis/Strahlung.aux
+++ b/Doering-PHD-Thesis/Strahlung.aux
@@ -96,7 +96,7 @@
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.3.4}Random Telegraph Signal}{43}{subsection.3.3.4}}
 \@writefile{lof}{\contentsline {figure}{\numberline {3.8}{\ignorespaces Ausgew\"ahltes Pixel mit Random Telegraph Signal \cite  {Doe08}\relax }}{44}{figure.caption.32}}
 \newlabel{fig:RTSBild}{{3.8}{44}{Ausgewähltes Pixel mit Random Telegraph Signal \cite {Doe08}\relax }{figure.caption.32}{}}
-\@writefile{toc}{\contentsline {chapter}{\numberline {4}Methoden zur Strahlenh\"arteuntersuchung 21.~Oktober 2013}{45}{chapter.4}}
+\@writefile{toc}{\contentsline {chapter}{\numberline {4}Methoden zur Strahlenh\"arteuntersuchung 1.~November 2013}{45}{chapter.4}}
 \@writefile{lof}{\addvspace {10\p@ }}
 \@writefile{lot}{\addvspace {10\p@ }}
 \@writefile{toc}{\contentsline {section}{\numberline {4.1}Experimenteller Aufbau}{45}{section.4.1}}
@@ -153,9 +153,10 @@
 \citation{Doe08}
 \@writefile{toc}{\contentsline {subsection}{\numberline {4.2.5}Fixed Pattern Noise}{63}{subsection.4.2.5}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {4.2.6}Fehltreffer}{63}{subsection.4.2.6}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {4.2.7}Cluster}{63}{subsection.4.2.7}}
+\newlabel{observablecluster}{{4.2.7}{63}{Cluster}{subsection.4.2.7}{}}
 \@writefile{lof}{\contentsline {figure}{\numberline {4.12}{\ignorespaces Summierte Ladungsverteilung eines Clusters.}}{64}{figure.caption.44}}
 \newlabel{fig:ClusterBeispiel}{{4.12}{64}{Summierte Ladungsverteilung eines Clusters}{figure.caption.44}{}}
-\@writefile{toc}{\contentsline {subsection}{\numberline {4.2.7}Cluster}{65}{subsection.4.2.7}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {4.2.8}Ladungsspektrum}{65}{subsection.4.2.8}}
 \@writefile{toc}{\contentsline {subsubsection}{\numberline {4.2.8.1}Photon-Quelle}{65}{subsubsection.4.2.8.1}}
 \@writefile{lof}{\contentsline {figure}{\numberline {4.13}{\ignorespaces Ladungsspektrum eines Fe-55-Strahlers.}}{66}{figure.caption.45}}
@@ -164,9 +165,9 @@
 \newlabel{fig:spectrum1425}{{4.14}{67}{Ladungsspektrum eines Fe-55-Strahlers bei drei verschiedenen Clustergrößen}{figure.caption.46}{}}
 \@writefile{lof}{\contentsline {figure}{\numberline {4.15}{\ignorespaces Ladungsspektrum des Seedpixels mit und ohne Vetotrigger}}{68}{figure.caption.47}}
 \newlabel{fig:Vetotrigger}{{4.15}{68}{Ladungsspektrum des Seedpixels mit und ohne Vetotrigger}{figure.caption.47}{}}
+\@writefile{toc}{\contentsline {paragraph}{\numberline {4.2.8.1.1}Vetotrigger auf das Seedpixel}{68}{figure.caption.47}}
 \@writefile{lof}{\contentsline {figure}{\numberline {4.16}{\ignorespaces Ladungsspekrum des Gesamtclusters}}{69}{figure.caption.48}}
 \newlabel{fig:WholeClusterTrigger}{{4.16}{69}{Ladungsspekrum des Gesamtclusters}{figure.caption.48}{}}
-\@writefile{toc}{\contentsline {paragraph}{\numberline {4.2.8.1.1}Vetotrigger auf das Seedpixel}{69}{figure.caption.47}}
 \@writefile{toc}{\contentsline {paragraph}{\numberline {4.2.8.1.2}Trigger auf Gesamtcluster}{69}{figure.caption.48}}
 \citation{DoeringMaster}
 \@writefile{toc}{\contentsline {paragraph}{\numberline {4.2.8.1.3}Fe-55-Quelle}{70}{paragraph.4.2.8.1.3}}
@@ -221,7 +222,7 @@
 \newlabel{fig:Mi18-gamma-neutron-anneal}{{4.26}{84}{Vergleich des Rauschens von Neutronen und Gamma bestrahlten Chips mit nur mit Gamma bestrahlten Chips als Funktion der Ausheilzeit}{figure.caption.58}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {4.4.1}Vergleich mit Co-60-bestrahlten Sensoren}{85}{subsection.4.4.1}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {4.4.2}Ausheilverhalten}{86}{subsection.4.4.2}}
-\@writefile{toc}{\contentsline {subsection}{\numberline {4.4.3}Zusammenfassung}{87}{subsection.4.4.3}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {4.4.3}Zusammenfassung}{86}{subsection.4.4.3}}
 \@writefile{toc}{\contentsline {section}{\numberline {4.5}Zusammenfassung}{87}{section.4.5}}
 \@setckpt{Strahlung}{
 \setcounter{page}{88}

diff --git a/Doering-PHD-Thesis/Strahlung.tex b/Doering-PHD-Thesis/Strahlung.tex
index 7be05ce0ac491cd7c51ff5490d79a4ea7d564683..8841c8b5de9fb6de662e7703b39e34860edee6cc 100755 (executable)
--- a/Doering-PHD-Thesis/Strahlung.tex
+++ b/Doering-PHD-Thesis/Strahlung.tex
@@ -188,7 +188,7 @@ Ein zweiter Strahlenh
 Die Testkarte, auf die der Chip gebondet ist, wird über Flachbandkabel an eine zweite, baugleiche Hilfskarte angeschlossen, die über eine Zwischenkarte (interface board) mit der Flex-Riokarte des National Instruments PXI-Systems verbunden ist. Die Datenanalyse wird anschließend mit ROOT durchgeführt.\newline
 \subsection{Automatische Datenaufnahme}
 Die automatische Datenaufnahme erleichtert die Durchführung systematischer Strahlenhärtestudien. Diese ermöglicht es die Matrizen eines Chips automatisch durchzumessen. Dazu werden in einer Datenbank die Messparameter festgelegt und ein Skript programmiert anhand dieser die JTAG-Kette, Auslesesoftware, Temperatur und externe Frequenz. Wünschenswert, allerdings noch nicht umgesetzt, ist eine automatische Positionierung der radioaktiven Quellen und Chipaustausch. \newline
-Das große Potential der automatischen Datenaufnahme für eine Strahlenhärtestudie wird an MIMOSA-32 deutlich. Dieser Chip hat 32 Matrizen, die bei mindestens drei Temperaturen vermessen werden müssen. Die Messung eines Fe-55-Spektrums erfordert 1 Million Auslesezyklen, so dass eine Messung vier Stunden dauert. Ohne automatische Datenaufnahme muss der Chip entsprechend alle vier Stunden neu programmiert werden, so dass pro Arbeitstag im Schnitt nur drei Messungen durchgeführt werden können. Die gesamte Messkampagne würde entsprechend $32\cdot3/3~\rm d=32~\rm d$ dauern. Die automatische Datenaufnahme übernimmt dies, so dass nach dem Start mit einem Mausklick nach $32\cdot3\cdot4~\rm h=384~\rm h=16~\rm d$ die Messungen durchgeführt sind.\newline
+Das große Potential der automatischen Datenaufnahme für eine Strahlenhärtestudie wird an MIMOSA-32 deutlich. Dieser Chip hat 32 Matrizen, die bei mindestens drei Betriebstemperaturen vermessen werden sollen. Die Messung eines Fe-55-Spektrums erfordert 1 Million Auslesezyklen, so dass eine Messung vier Stunden dauert. Ohne automatische Datenaufnahme muss der Chip entsprechend alle vier Stunden neu programmiert werden, so dass pro Arbeitstag im Schnitt nur drei Messungen durchgeführt werden können. Die gesamte Messkampagne würde entsprechend $32\cdot3/3~\rm d=32~\rm d$ dauern. Die automatische Datenaufnahme übernimmt dies, so dass nach dem Start mit einem Mausklick nach $32\cdot3\cdot4~\rm h=384~\rm h=16~\rm d$ die Messungen durchgeführt sind.\newline
 Auch systematische Studien werden vereinfacht. Beispielsweise sollte die Integrationszeit systematisch über den externen Frequenzgenerator variiert werden. Eine Messung benötigte hier zwar nur $1~\rm k$ Auslesezyklen und damit nur wenige Minuten, allerdings waren 90 Messungen durchzuführen, was in einer Messkampagne von fünf Stunden resultiert, in der eine Arbeitskraft nur mit Messungen Durchführen gebunden wird. Die automatische Datenaufnahme kann auch diese Aufgabe übernehmen.\newline
 Darüber hinaus werden menschliche Fehler in der Durchführung des Messprotokolls weitesgehend vermieden und eventuell auftretende Fehler sind besser reproduzierbar oder dank umfassender automatischen Dokumentation leicht nachvollziehbar.\newline  
 Das Skript führt im USB-System folgende Routine aus:
@@ -250,7 +250,7 @@ Bei allen K
 \begin{figure}
 \centering
                \includegraphics[width=1\textwidth]{BilderHR/Mi18-temperature-measurement-infrared.pdf}
-               \caption[Temperatur des Chips und Metallblocks]{Gemessene Temperatur als Funktion der Kühlflüssigkeitstemperatur, gemessen mit einer Infrarotkamera auf der Oberfläche des Sensors (rote Kreise) und mit einem Temperatursensor PT100 (schwarze Quadrate). Bei einer Kühlflüssigkeitstemperatur von $T=-70~{}^{\circ}\rm C$ wird eine absolute Temperatur von $T=-40~{}^{\circ}\rm C$ am Metallblock und $T=-34~{}^{\circ}\rm C$ am Chip erreicht.}
+               \caption[Temperatur des Chips und Metallblocks]{Gemessene Temperatur als Funktion der Kühlflüssigkeitstemperatur, gemessen mit einer Infrarotkamera auf der Oberfläche des Sensors (rote Kreise) und mit einem Temperatursensor PT100 (schwarze Quadrate). Bei einer Kühlflüssigkeitstemperatur von $T=-70~{}^{\circ}\rm C$ wird eine Temperatur von $T=-40~{}^{\circ}\rm C$ am Metallblock und $T=-34~{}^{\circ}\rm C$ am Chip erreicht.}
        \label{fig:Mi18-temperature-measurement-infrared}
 \end{figure}
 \begin{figure}
@@ -259,9 +259,10 @@ Bei allen K
                \caption[Infrarotbild eines Chips]{Links: Infrarotbild eines MIMOSA-18 in der Messapparatur. Mit der Infrarotkamera lässt die Temperatur auf dem Chip und der umgebenen PCB-Karte bestimmen. Bei einer Kühlflüssigkeitstemperatur von $T_{Kuehlung}=-70~{}^{\circ}\rm C$  werden $T_{Infrarot}=-34~{}^{\circ}\rm C$ erreicht. Rechts: Der MIMOSA-18 wurde mit schwarzem Kameralack lackiert um eine Referenzfarbe für die Infrarotkamera zu garantieren.}
        \label{fig:Mi18-Infraredbild}
 \end{figure}
-Die Chips werden mit einem Huberkühlsystem temperiert, welches Kühlflüssigkeitstemperaturen bis $T=-90~{}^{\circ}\rm C$ ermöglicht. Die allerdings offene Frage ist, wie groß die Verluste in der Kühlkette sind und wie groß damit schließlich die Temperatur am Sensor ist. Es wurde in \cite{DoeringMaster} gezeigt, dass mit dem verwendeten Kühlsystem bei sorgfältiger Durchführung des Kühlprotokolls reproduzierbare Leckstrommessungen mit $<1\%$ Genauigkeit durchgeführt werden können und da der Leckstrom empfindlich von der Temperatur abhängt, auch indirekt die Temperatur gut reproduziert werden kann. Eine Aussage über die absolute Temperatur wurde aber in \cite{DoeringMaster,Doe08} nicht gemacht. Es wurden nur Messungen mit einem PT100 am Metallblock durchgeführt, die allerdings nur die Temperatur des Metallblocks und nicht des Sensors wiedergeben. Dies ist insofern wichtig, da der Sensor ebenfalls eine Wärmequelle ist, die gekühlt werden muss. Entsprechend ist die Temperatur des Sensors deutlich höher als die der Kühlflüssigkeit und des Metallblocks. Damit ist die absolute Temperatur des Chips als Funktion der Kühlflüssigkeitstemperatur eine offene Frage. \newline
+Die Chips werden mit einem Huberkühlsystem temperiert, welches Kühlflüssigkeitstemperaturen bis $T=-90~{}^{\circ}\rm C$ ermöglicht. Allerdings treten Verluste in der Kühlkette, so dass diese Temperatur auf dem Sensor in der Regel nicht ganz erreicht wird. Eine zusätzliche Wärmequelle direkt am Sensor ist auch die Ausleselektronik der PCB-Karte. Ihre Abwärme muss auch vom Kühlsystem abtransportiert werden, was die für den Sensor zur Verfügung stehende Kühlleistung herabsetzt.\newline
+Es wurde in \cite{DoeringMaster} gezeigt, dass mit dem verwendeten Kühlsystem bei sorgfältiger Durchführung des Kühlprotokolls reproduzierbare Leckstrommessungen mit $<1\%$ Genauigkeit durchgeführt werden können. Da der Leckstrom empfindlich von der Temperatur abhängt, kann damit auf eine gute Reproduzierbarkeit der Temperatur geschlossen werden. Eine Aussage über die exakte Temperatur wurde aber in \cite{DoeringMaster,Doe08} nicht gemacht. Es wurden nur Messungen mit einem Temperatursensor PT100 am Metallblock durchgeführt, die allerdings nur die Temperatur des Metallblocks und nicht des Sensors wiedergeben. Dies ist insofern wichtig, da der Sensor ebenfalls eine Wärmequelle ist, die gekühlt werden muss. Entsprechend ist die Temperatur des Sensors deutlich höher als die der Kühlflüssigkeit und des Metallblocks. Damit ist die exakte Temperatur des Chips als Funktion der Kühlflüssigkeitstemperatur eine offene Frage. \newline
 Im Rahmen dieser Arbeit wurde zum ersten Mal die Temperatur direkt auf dem Chip mit einer Infrarotkamera gemessen. Abbildung \ref{fig:Mi18-Infraredbild} links zeigt den Chip im Infrarotbild. Dazu wurde ein MIMOSA-18 mit einem schwarzen Kameralack besprüht um eine für die Infrarottemperaturmessung erforderliche Referenzfläche zu schaffen (Abbildung \ref{fig:Mi18-Infraredbild} rechts). Der Lack war elektrisch nicht-leitend, so dass der Chip nach der Lackierung vollständig funktionsfähig war und während der Temperaturmessung auch betrieben wurde.\newline 
-Die Abhängigkeit der gemessenen Temperatur von der Temperatur der Kühlflüssigkeit zeigt Abbildung \ref{fig:Mi18-temperature-measurement-infrared}. Die Temperatur der Kühlflüssigkeit betrug $-20~{}^{\circ}\rm C$ bis $T=-70~{}^{\circ}\rm C$, während mit der Infrarotkamera eine Temperatur zwischen $-3~{}^{\circ}\rm C$ und $-34~{}^{\circ}\rm C$ gemessen wurde. Ebenfalls eingezeichnet ist die Temperaturmessung des Metallblocks mit Hilfe des PT100. Die Graphen sind über den großen Bereich parallel, womit das Hubersystem über den gesamten Kühlbereich über eine ausgezeichnete Kühlleistung verfügt. Damit zeigt sich, dass die frühere Annahme einer zwar nicht genau bekannten, aber gut reproduzierbaren Temperatur gerechtfertigt war. Es gibt nur einen Offset zur Temperatur am Metallblock. Der Offset beträgt $5\pm1~\rm K$. Damit ist nun die Temperatur an der Oberfläche des Chips bekannt.
+Die Abhängigkeit der gemessenen Temperatur von der Temperatur der Kühlflüssigkeit zeigt Abbildung \ref{fig:Mi18-temperature-measurement-infrared}. Die Temperatur der Kühlflüssigkeit betrug $-20~{}^{\circ}\rm C$ bis $T=-70~{}^{\circ}\rm C$, während mit der Infrarotkamera eine Temperatur zwischen $-3~{}^{\circ}\rm C$ und $-34~{}^{\circ}\rm C$ gemessen wurde. Ebenfalls eingezeichnet ist die Temperaturmessung des Metallblocks mit Hilfe des Temperatursensors. Die Graphen sind parallel, womit das Hubersystem über den gesamten Kühlbereich über eine ausgezeichnete Kühlleistung verfügt. Damit zeigt sich, dass die frühere Annahme einer zwar nicht genau bekannten, aber gut reproduzierbaren Temperatur gerechtfertigt war. Es gibt nur einen Offset zur Temperatur am Metallblock. Der Offset beträgt $5\pm1~\rm K$. Damit ist nun die Temperatur an der Oberfläche des Chips bekannt.
 \subsection{Radioaktive Quellen}
 Zur Qualifizierung der Sensoren stehen die Photonenquellen Fe-55 und Cd-109 sowie die Elektronenquellen Ru-106 und Sr-90 zur Verfügung. Gelagert werden die Quellen in einem Wandtresor aus $5~\rm cm$ dickem Blei. Die gemessene Dosisleistung bei geschlossenem Tresor beträgt $<1~\rm \upmu Sv/h$.
 \begin{figure}
@@ -277,9 +278,9 @@ Zur Qualifizierung der Sensoren stehen die Photonenquellen Fe-55 und Cd-109 sowi
        \label{fig:QuellenhalterungBeta}
 \end{figure}
 \subsubsection{Photonenquellen}
-Die Photonenquellen Fe-55 und Cd-109 sind einem Zylinder mit den Dimensionen $12,7~\rm mm ~\times 5,08~\rm mm$ eingeschlossen (Abbildung \ref{fig:QuellenhalterungPhoton}) und sind zusätzlich durch ein Messinggehäuse mit einer minimalen Dicke von $2~\rm mm$ abgeschirmt. Dieses hat nach unten eine Austrittsöffnung, die während des Transports durch einen Einschub abgeschirmt wird. Für Cd-109 betrug die direkte Dosisleistung am Referenzdatum 01.05.2011 direkt an der geöffneten Austrittsöffnung $5~\rm mSv/h$, am Gehäuse $15~\rm \upmu Sv/h$ sowie unter einer weiteren Transporthaube $<1~\rm \upmu Sv/h$. Für Fe-55 betrug die direkte Dosisleistung am Referenzdatum 21.05.2005 direkt an der geöffneten Austrittsöffnung $45~\rm mSv/h$ und am Gehäuse $3~\rm \upmu Sv/h$.
+Die Photonenquellen Fe-55 und Cd-109 sind in einem Zylinder mit den Dimensionen $12,7~\rm mm ~\times 5,08~\rm mm$ eingeschlossen (Abbildung \ref{fig:QuellenhalterungPhoton}) und sind zusätzlich durch ein Messinggehäuse mit einer minimalen Dicke von $2~\rm mm$ abgeschirmt. Dieses hat nach unten eine Austrittsöffnung, die während des Transports durch einen Einschub abgeschirmt wird. Für Cd-109 betrug die direkte Dosisleistung am Referenzdatum 01.05.2011 direkt an der geöffneten Austrittsöffnung $5~\rm mSv/h$, am Gehäuse $15~\rm \upmu Sv/h$ sowie unter einer weiteren Transporthaube $<1~\rm \upmu Sv/h$. Für Fe-55 betrug die direkte Dosisleistung am Referenzdatum 21.05.2005 direkt an der geöffneten Austrittsöffnung $45~\rm mSv/h$ und am Gehäuse $3~\rm \upmu Sv/h$.
 \subsubsection{Elektronenquellen}
-Die Elektronenquellen Ru-106 und Sr-90 sind einem Zylinder mit den Dimensionen $7.92~\rm mm \times 5,08~\rm mm$ eingeschlossen (Abbildung \ref{fig:QuellenhalterungBeta}). Ein Gehäuse aus mindestens $18~\rm mm$ Plexiglas dient zur Abbremsung der Elektronen. Zusätzlich ist das Plexiglas mit einem $5~\rm mm$ dicken Aluminiumgehäuse zur Absorption sekundärer Photonen umgeben. Für Ru-106 betrug die direkte Dosisleistung am Referenzdatum 01.05.2011 direkt an der geöffneten Austrittsöffnung $1.5~\rm mSv/h$ und am Gehäuse $40~\rm \upmu Sv/h$. Für Sr-90 betrug die direkte Dosisleistung am Referenzdatum 09.09.2011 direkt an der geöffneten Austrittsöffnung $2.7~\rm mSv/h$ und am Gehäuse $7~\rm \upmu Sv/h$.        
+Die Elektronenquellen Ru-106 und Sr-90 sind in einem Zylinder mit den Dimensionen $7.92~\rm mm \times 5,08~\rm mm$ eingeschlossen (Abbildung \ref{fig:QuellenhalterungBeta}). Ein Gehäuse aus mindestens $18~\rm mm$ Plexiglas dient zur Abbremsung der Elektronen. Zusätzlich ist das Plexiglas mit einem $5~\rm mm$ dicken Aluminiumgehäuse zur Absorption sekundärer Photonen umgeben. Für Ru-106 betrug die direkte Dosisleistung am Referenzdatum 01.05.2011 direkt an der geöffneten Austrittsöffnung $1.5~\rm mSv/h$ und am Gehäuse $40~\rm \upmu Sv/h$. Für Sr-90 betrug die direkte Dosisleistung am Referenzdatum 09.09.2011 direkt an der geöffneten Austrittsöffnung $2.7~\rm mSv/h$ und am Gehäuse $7~\rm \upmu Sv/h$.        
 \clearpage
 
 \section{Observablen}
@@ -299,8 +300,8 @@ Die Elektronenquellen Ru-106 und Sr-90 sind einem Zylinder mit den Dimensionen $
 Aus dem Signal nach Anwendung von CDS lassen sich im Folgenden weitere Observablen extrahieren um so quantitative Aussagen über die Leistungsfähigkeit eines Sensors, insbesondere nach Bestrahlung zu erhalten. Abbildung \ref{fig:hitsignal} zeigt ein typisches, gemessenes Signal nach Anwendung von CDS, was im Folgenden im Detail analysiert werden wird. 
 
 \subsection{Das CDS-Signal}
-Das CDS-Signal der Pixel ist die Ausgangsposition, aus der alle Observablen abgeleitet werden. Das CDS-Signal eines Pixels ohne Signalladung zeigt Abbildung \ref{fig:CDS_Achsen}. In jedem Zeitabschnitt (frame) wird der Ladungseintrag des Pixels als CDS-Signal in der Einheit ADC gemessen. Es ergibt der Graph, der den Ladungseintrag auf der linken y-Achse als Funktion der Zeitabschnitte auf der unteren x-Achse zeigt. Wenn die Verstärkung bekannt ist (siehe Abschnitt \ref{kalibrierung}), kann der Ladungseintrag in eine Anzahl von Elektronen umgerechnet werden (rechte, kursive y-Achse). Diese Elektronen werden in der Integrationszeit der Länge $t_{int}$ gesammelt. Es ergibt sich also ein elektrischer Strom in der Größenordnung von wenigen $fA$. Das Pixel hat zum Beispiel nach 10 Sekunden Messzeit im Zeitabschnitt 200 23 ADC Ladung gesammelt, das entspricht 250 Elektronen oder einen Strom von 11 fA. \newline
-Bei der in dieser Arbeit verwendeten Ausleseelektronik handelt es sich um eine vereinfachte Variante zum Testen der Strahlenhärte der Sensoren. Damit ist auch bei SB-Pixeln keine kontinuierliche Auslese möglich. Das bedeutet, dass sich an Zeitabschnitt $i$, nicht der Zeitabschnitt $i+1$ direkt anschließt, sondern das Pixel für eine Totzeit $t_{totzeit}$ nicht ausgelesen wird. Folglich lässt sich die Messzeit nicht aus der Länge der Integrationszeit $t_{int}$ und der Anzahl der Zeitabschnitte $N$ berechnen. Die Messzeit $t_{Mess}$ ergibt sich damit zu:
+Das CDS-Signal der Pixel ist die Ausgangsposition, aus der alle Observablen abgeleitet werden. Das CDS-Signal eines Pixels ohne Signalladung zeigt Abbildung \ref{fig:CDS_Achsen}. In jedem Zeitabschnitt (frame) wird der Ladungseintrag des Pixels als CDS-Signal in der Einheit ADC gemessen. Es ergibt der Graph, der den Ladungseintrag auf der linken y-Achse als Funktion der Zeitabschnitte auf der unteren x-Achse zeigt. Wenn die Verstärkung bekannt ist (siehe Abschnitt \ref{kalibrierung}), kann der Ladungseintrag in eine Anzahl von Elektronen umgerechnet werden (rechte, kursive y-Achse). Diese Elektronen werden in der Integrationszeit der Länge $t_{int}$ gesammelt. Es ergibt sich also ein elektrischer Strom in der Größenordnung von wenigen $fA$. Das Pixel hat zum Beispiel im Zeitabschnitt 200, was 10 Sekunden Messzeit entspricht, 23 ADC Ladung gesammelt, das entspricht 250 Elektronen oder einen Strom von 11 fA. \newline
+Bei der in dieser Arbeit verwendeten Ausleseelektronik handelt es sich um eine vereinfachte Variante zum Testen der Strahlenhärte der Sensoren. Damit ist auch bei SB-Pixeln keine kontinuierliche Auslese möglich. Das bedeutet, dass sich an Zeitabschnitt $i$, nicht der Zeitabschnitt $i+1$ direkt anschließt, sondern das Pixel für eine Totzeit $t_{totzeit}$ nicht ausgelesen wird. Folglich lässt sich die Messzeit nicht aus der Länge der Integrationszeit $t_{int}$ und der Anzahl der Zeitabschnitte $N$ berechnen. Die Messzeit $t_{Mess}$ ergibt sich sondern zu:
 \begin{equation}
 t_{Mess}=t_{int}\cdot N+t_{totzeit}
 \label{messzeitideal}  
@@ -350,15 +351,16 @@ Die Quellen dieser Fluktuationen werden in \cite{Dep02} ausgef
 \subsection{Konzept Schwelle}
 Um Teilchendurchgänge aus dem CDS-Signal zu identifizieren, muss ein Kriterium entwickelt werden, nach dem ein Ladungseintrag von einem Teilchen kommt. Eine potentielle Signalladung überlagert dabei die Grundlinie. Naheliegend ist die höchsten Ladungseinträge als Signalladung zu postulieren. Günstiger ist es dagegen erst einmal das CDS-Signal zu analysieren, wenn keine Signalladung erwartet wird. Wenn im Vergleich zu einer Messung, in der Signalladung erwartet wird, Abweichungen des Sensors beobachtet werden, sind diese voraussichtlich auf Teilchendurchgänge zurückzuführen.
 In MAPS-Sensoren sind Teilchendurchgänge als Peaks von der Grundlinie identifizierbar (siehe Abbildung \ref{fig:hitsignal}). Als Kriterium um die Signalladung zuverlässig zu identifizieren, wird eine Schwelle definiert. Ist der Ladungseintrag größer als die Schwelle, wird ein Treffer postuliert und kann in weiteren Analyseschritten analysiert werden.\newline
-Für die Festlegung des Werts der Schwelle, existieren verschiedene Ansätze. Es kann für jedes Pixel eine individuelle sich dem Rauschen anpassende Schwelle gewählt werden. Dazu wird das Rauschen eines Pixels einige Auslesezyklen vor einem potentiellen Treffer analysiert. Es wird eine Standardabweichung gebildet, von deren Berechnung die höchsten Werte ausgeschlossen werden. Denn hier könnte es sich um Signalladung eines weiteren Treffers handeln. Von diesem bestimmten Rauschwert wird die Schwelle als $5\sigma$-Kriterium gewählt, was einer Fehltrefferrate von 0,023 \% pro Pixel und Auslesezyklus entspricht. Dadurch wird ein Anstieg der Fehltreffer durch ein höheres Rauschen ausgeglichen, solange dieses gaußförmig ist. Eine weitere Möglichkeit ist die Festlegung einer festen Schwelle. Alle Ladungseinträge, die diese Schwelle überschreiten, werden als Treffer postuliert. Entsprechend steigt die Anzahl an Fehltreffern mit dem Rauschen. Der Vorteil ist, dass eine feste Schwelle in in-Chip-Diskriminatoren verwirklicht werden kann und damit die Datenrate bereits im Chip reduziert werden kann. Die Schwelle wird je nach Verwirklichung dabei fest vorgegeben für ein Pixel, eine Zeile, Matrix oder gar gesamten Sensor, abhängig davon, wie viele Pixel über einen Diskriminator ausgelesen werden. Entsprechend entscheidend ist eine möglichst homogene Pixelverteilung bei gleichzeitig möglichst niedrigem Rauschen. Eine zu hoch gewählte Schwelle maskiert Signalladung, eine zu niedrig gewählte Schwelle generiert Fehltreffer aufgrund des Rauschens. Hat ein Pixel ein im Vergleich zu anderen Pixel ein hohes Rauschen, so wird dieses substantiell viele Fehltreffer generieren, da die Schwelle für dieses spezielle Pixel nicht angepasst werden kann.  
+Für die Festlegung des Werts der Schwelle, existieren verschiedene Ansätze. Es kann für jedes Pixel eine individuelle sich dem Rauschen anpassende Schwelle gewählt werden. Dazu wird das Rauschen eines Pixels einige Auslesezyklen vor einem potentiellen Treffer analysiert. Es wird eine Standardabweichung gebildet, von deren Berechnung die höchsten Werte ausgeschlossen werden. Denn hier könnte es sich um Signalladung eines weiteren Treffers handeln. Von diesem bestimmten Rauschwert wird die Schwelle als $5\sigma$-Kriterium gewählt, was einer Fehltrefferrate von 0,023 \% pro Pixel und Auslesezyklus entspricht. Dadurch wird ein Anstieg der Fehltreffer durch ein höheres Rauschen ausgeglichen, solange dieses gaußförmig ist. Eine weitere Möglichkeit ist die Festlegung einer festen Schwelle. Alle Ladungseinträge, die diese Schwelle überschreiten, werden als Treffer postuliert. Entsprechend steigt die Anzahl an Fehltreffern mit dem Rauschen. Der Vorteil ist, dass eine feste Schwelle in in-Chip-Diskriminatoren verwirklicht werden kann und damit die Datenrate bereits im Chip reduziert werden kann. Die Schwelle wird je nach Verwirklichung dabei fest vorgegeben für ein Pixel, eine Zeile, Matrix oder gar gesamten Sensor, abhängig davon, wie viele Pixel über einen Diskriminator ausgelesen werden. Entsprechend entscheidend ist eine möglichst homogene Pixelverteilung bei gleichzeitig möglichst niedrigem Rauschen. Eine zu hoch gewählte Schwelle maskiert Signalladung, eine zu niedrig gewählte Schwelle unterdrückt nicht die Fehltreffer aufgrund des Rauschens. Hat ein Pixel ein im Vergleich zu anderen Pixel ein hohes Rauschen, so wird dieses substantiell viele Fehltreffer generieren, da die Schwelle für dieses spezielle Pixel nicht angepasst werden kann.  
 \subsection{Fixed Pattern Noise}
-Neben der eigentlichen Grundlinie ist die Breite der Verteilung, welche die Abweichung der einzelnen Pixel von der Grundlinie darstellt, interessant. Diese spiegelt hauptsächlich die Herstellungstoleranzen der Transistoren der Pixel wider. 
-Solange für jedes Pixel eine spezifische Schwelle angelegt werden kann, kann dieser Effekt vollständig ausgeglichen werden. Bei der großen Anzahl an Pixeln ist es allerdings zu aufwändig jedem Pixel eine individuelle Schwelle zuzuteilen, so dass letztendlich ein Schwellenwert für eine Gruppe von Pixeln definiert wird. Dies setzt die Annahme voraus, dass die Variationen der Grundlinie der Pixel nicht zu stark ist, die Breite der Verteilung damit nicht zu groß ist. Kritisch wäre hier vor allem eine asymmetrische Verschiebung der Grundlinie der Pixel, da in diesem Fall die Schwelle nicht mehr für alle Pixel passend ist. Entsprechend wird die Breite der Verteilung als "`Fixed Pattern Noise"' bei Strahlenhärteuntersuchungen analysiert. 
+Neben der eigentlichen Grundlinie ist die Breite der Verteilung interessant, welche die Abweichung der einzelnen Pixel von der Grundlinie darstellt. Diese spiegelt hauptsächlich die Herstellungstoleranzen der Transistoren der Pixel wider. 
+Solange für jedes Pixel eine spezifische Schwelle angelegt werden kann, kann dieser Effekt vollständig ausgeglichen werden. Bei der großen Anzahl an Pixeln ist es allerdings zu aufwändig jedem Pixel eine individuelle Schwelle zuzuteilen, so dass letztendlich ein Schwellenwert für eine Gruppe von Pixeln definiert wird. Dies setzt die Annahme voraus, dass die Variationen der Grundlinie der Pixel nicht zu stark und damit die Breite der Verteilung damit nicht zu groß ist. Kritisch ist hier vor allem eine asymmetrische Verschiebung der Grundlinie der Pixel, da in diesem Fall die Schwelle nicht mehr für alle Pixel passend ist. 
 
 \subsection{Fehltreffer}
-Das Signal wird durch Anlegen einer Schwelle vom Rauschen getrennt. Wenn die Schwelle zu niedrig ist, kann diese allerdings auch aufgrund des Rauschens überschritten werden. Dadurch wird ein Fehltreffer generiert. Solange das Signal groß genug ist und das Rauschen gaußförmig ist, können diese Fehltreffer durch Anlegen einer höheren Schwelle unterdrückt werden. Die Observable Fehltrefferrate, sprich Fehltreffer pro Auslesezyklus und Pixel, sinkt. In \cite{Doe08} wurde allerdings Random Telegraph Signal in MAPS beobachtet, welches in einem nicht-gaußförmigen Rauschen einzelner Pixel resultiert und eine große Fehltrefferrate besonders nach Bestrahlung und bei hohen Betriebstemperaturen zur Folge haben kann, welche auch nicht immer zuverlässig durch Anlegen einer höheren Schwelle verringert werden kann, sondern andere Konzepte erfordert.\newline
-Im Fall von Random Telegraph Signal kann es nach \cite{Doe08} eine Strategie sein Pixel mit Random Telegraph Signal zu maskieren. Da Teilchendurchgänge oft Cluster (siehe nächsten Abschnitt) bilden, ist ein weiteres Konzept Fehltreffer zu unterdrücken das Betrachten von benachbarten Pixel, ob diese ebenfalls einen Ladungseintrag aufweisen. Falls nicht, wird der Treffer in diesem Konzept verworfen.     
+Das Signal wird durch Anlegen einer Schwelle vom Rauschen getrennt. Wenn die Schwelle zu niedrig ist, kann diese allerdings auch aufgrund des Rauschens überschritten werden. Dadurch wird ein Fehltreffer generiert. Solange das Signal groß genug ist und das Rauschen gaußförmig ist, können diese Fehltreffer durch Anlegen einer höheren Schwelle unterdrückt werden. Die Observable Fehltrefferrate, sprich Fehltreffer pro Auslesezyklus und Pixel, sinkt. In \cite{Doe08} wurde allerdings das Random Telegraph Signal in MAPS beobachtet, welches in einem nicht-gaußförmigen Rauschen einzelner Pixel resultiert und eine große Fehltrefferrate besonders nach Bestrahlung und bei hohen Betriebstemperaturen zur Folge haben kann, welche auch nicht immer zuverlässig durch Anlegen einer höheren Schwelle verringert werden kann, sondern andere Konzepte erfordert.\newline
+Im Fall von Random Telegraph Signal kann es nach \cite{Doe08} eine Strategie sein Pixel mit Random Telegraph Signal zu maskieren. Da Teilchendurchgänge oft Cluster (siehe nächsten Abschnitt \ref{observablecluster}) bilden, ist ein weiteres Konzept Fehltreffer zu unterdrücken das Betrachten von benachbarten Pixel, ob diese ebenfalls einen Ladungseintrag aufweisen. Falls nicht, wird der Treffer in diesem Konzept verworfen.     
 \subsection{Cluster}
+\label{observablecluster}
 \begin{figure}
        \centering
                \includegraphics[width=1\textwidth]{Bilder/ClusterBeispiel.pdf}
@@ -379,7 +381,7 @@ Die Signalh
 Photonen konvertieren lokal in der Epitaxieschicht. Generierte Signalelektronen diffundieren zu den Dioden. Die Größe des Ladungseintrages hängt von der Entfernung zu den Dioden ab. Damit lässt sich die Epitaxieschicht durch Analysieren des Ladungsspektrums studieren. \newline
 Konvertiert das Photon in der verarmten Zone in der Nähe einer Diode, werden sämtliche Signalelektronen von einem Pixel gesammelt. Eine Diffusion in benachbarte Pixel findet nicht statt. Es kommt zur Ausbildung eines Peaks bei großen Signalhöhen, Kalibrationspeak genannt (in Abbildung \ref{fig:FeSpektrum} bei $160~\rm ADC$ Ladungseintrag).\newline
 Je weiter die Konversion von einer Diode entfernt stattfindet, desto mehr Signalelektronen diffundieren in benachbarten Pixel. Der Ladungseintrag im Seedpixel sinkt. Dabei bildet sich ein breiter Peak aus, Sammelpeak genannt (in Abbildung \ref{fig:FeSpektrum} bei $35-90~\rm ADC$ Ladungseintrag).\newline
-Am niedrigen Ende des Spektrums (Abbildung \ref{fig:FeSpektrum} bei $<35~\rm ADC$ Ladungseintrag) wird ein exponentieller Anstieg beobachtet, bis die Ladungseinträge durch die Schwelle abgeschnitten werden. In diesem Fall ist die Schwelle eine variable Schwelle, abhängig vom Rauschen der einzelnen Pixel. Entsprechend ist diese nicht scharf.\newline
+Am niedrigen Ende des Spektrums (Abbildung \ref{fig:FeSpektrum} bei $<35~\rm ADC$ Ladungseintrag) wird ein exponentieller Anstieg beobachtet, bis die Ladungseinträge durch die Schwelle abgeschnitten werden. In diesem Fall ist die Schwelle variabel und abhängig vom Rauschen der einzelnen Pixel. Entsprechend ist diese nicht scharf.\newline
 Der Anstieg kommt von Konversionen im Substrate und P-Well. Von diesen erreichen nur ein Teil der Signalelektronen die Epitaxieschicht, in der sie nachgewiesen können. Der Anteil hängt exponentiell von der Tiefe in der hoch p-dotierten Schicht ab.\newline
 Damit können drei Bereiche im Sensor separiert und ihr Verhalten in Abhängigkeit von Temperatur, Bestrahlung etc. studiert werden.\newline 
 Dabei durchqueren Signalelektronen des Sammelpeaks auch die verarmte Zone sowie Substratetreffer sowohl verarmte Zone als auch Epitaxieschicht. Sie werden also auch von Effekten in dieser beeinflusst.\newline
@@ -391,9 +393,9 @@ Der Vorteil an Photonen ist deshalb, dass sie lokal konvertieren und eine defini
        \caption[Ladungsspektrum eines Fe-55-Strahlers bei drei verschiedenen Clustergrößen]{Ladungsspektrum eines Fe-55-Strahlers bei drei verschiedenen Clustergrößen: 1 (rote durchgehende Linie), 4 (blaue gestrichene Linie) und 25 (schwarze Fläche) Pixel. Der große Peak wandert mit größerer Clustergröße zu höherer gesammelter Ladung. Der kleine Kalibrationspeak bei einem Wert von 160 Kanälen gibt die maximal sammelbare Ladung an. }
        \label{fig:spectrum1425}
 \end{figure}
-Wird die Ladung von Nachbarpixeln hinzusummiert, ergibt sich ein Ladungsspektrum für verschiedene Clustergrößen (Abbildung \ref{fig:spectrum1425}). Je größer die Clustergröße, desto mehr Ladungen werden einer Konversion zugeordnet, bis bei einer genügend großen Clustergröße alle in der Epitaxieschicht deponierten Ladungen nachgewiesen werden.\newline
-Umgekehrt argumentiert, weisen zu niedrige Einträge auf einen Verlust von Signalladung z.B. durch Rekombinationen in der Epitaxieschicht oder im Substrate hin. Für die unbestrahlte Epitaxieschicht kann angenommen werden, dass nahezu alle deponierten Ladungstrager von einem hinreichend großen Cluster gesammelt werden. Substratetreffer rekombinieren dagegen auf ihrem Weg durch das Substrate bis sie die Epitaxieschicht erreichen. \newline    
-Die X-Achse kann auf drei verschiedene Arten dargestellt werden. Im Rohspektrum wird erstens die Signalhöhe in der arbiträren Einheit ADC angegeben. Diese kann zweitens mit dem Kalibrationspeak in Elektronen umgerechnet werden. Dieser entspricht $100\%$ Ladungssammlungseffizienz. Entsprechend kann drittens das Spektrum darauf normiert werden.\newline
+Wird die Ladung von Nachbarpixeln hinzusummiert, ergibt sich ein Ladungsspektrum für verschiedene Clustergrößen (Abbildung \ref{fig:spectrum1425}). Je größer der Cluster, desto mehr Ladungen werden einer Konversion zugeordnet, bis bei genügend großen Cluster alle in der Epitaxieschicht freigesetzten Ladungen nachgewiesen werden.\newline
+Umgekehrt argumentiert, weisen zu niedrige Einträge auf einen Verlust von Signalladung z.B. durch Rekombinationen in der Epitaxieschicht oder im Substrate hin. Für die unbestrahlte Epitaxieschicht kann angenommen werden, dass nahezu alle freigesetzten Ladungsträger von einem hinreichend großen Cluster gesammelt werden. Substratetreffer rekombinieren dagegen auf ihrem Weg durch das Substrate bis sie die Epitaxieschicht erreichen. \newline    
+Die X-Achse kann auf drei verschiedene Arten dargestellt werden. Erstens kann die Signalhöhe in der arbiträren Einheit ADC angegeben werden. Diese kann zweitens mit dem Kalibrationspeak in Elektronen umgerechnet werden. Dieser entspricht $100\%$ Ladungssammlungseffizienz. Entsprechend kann drittens das Spektrum darauf normiert werden.\newline
 Die Y-Achse gibt die gesammelten Einträge während einer Messung wieder. Diese können auf die Messzeit, Pixel, Quelleneinstrahlintensität sowie Integrationszeit normiert werden. Werden mehrere Spektren verglichen, wird die gleiche Normierung angewendet. \newline
 \paragraph{Vetotrigger auf das Seedpixel}
 \begin{figure}
@@ -410,15 +412,15 @@ F
        \caption[Ladungsspekrum des Gesamtclusters]{Ladungsspektrum des Seedpixels, des gesamten Clusters und des resultierenden Spektrums des Seedpixels, wenn alle Cluster mit einer Gesamtladung von >240ADC verworfen werden. Es bleiben nur Ladungseinträge von Treffern im Substrate und P-Senke übrig. }
        \label{fig:WholeClusterTrigger}
 \end{figure} 
-Photonenquellen deponieren einen wohldefinierten Energiebetrag. Über den Kalibrationspeak kann dieser Energiebetrag kalibriert werden. Die angeregten Signalelektronen diffundieren in der Epitaxieschicht und werden von verschiedenen Pixel gesammelt. Wird aus diesen Pixel der Cluster bestimmt, kann dieser Energiebetrag rekonstruiert werden. Abbildung \ref{fig:WholeClusterTrigger} zeigt das Spektrum eines 25-Pixel-Clusters eines unbestrahlten Sensors im Vergleich zum Spektrum der Seedpixel. 93\% der Cluster haben einen Ladungseintrag von >240 ADC in der Nähe des Kalibrationspeaks und haben damit die gesamte vom Photon deponierte Ladung gesammelt. Nun werden Cluster in dem Peak verworfen und das Spektrum des Seedpixels betrachtet (Trigger Cluster-25<240 ADC). Es sind nur Einträge bei niedrigen Werten vorhanden. Diese können mit Substratetreffern identifiziert werden. Ein Teil ihrer Ladung rekombiniert im Substrate, die Gesamtladung des Cluster ist damit kleiner als die Triggerbedingung. \newline
+Photonenquellen deponieren einen wohldefinierten Energiebetrag. Über den Kalibrationspeak kann dieser Energiebetrag kalibriert werden. Die angeregten Signalelektronen diffundieren in der Epitaxieschicht und werden von verschiedenen Pixel gesammelt. Wird aus diesen Pixel der Cluster bestimmt, kann dieser Energiebetrag rekonstruiert werden. Abbildung \ref{fig:WholeClusterTrigger} zeigt das Spektrum eines 25-Pixel-Clusters eines unbestrahlten Sensors im Vergleich zum Spektrum der Seedpixel. 93\% der Cluster haben einen Ladungseintrag von >240 ADC in der Nähe des Kalibrationspeaks und haben damit die gesamte vom Photon freigesetzte Ladung gesammelt. Nun werden Einträge im Peak verworfen und das Spektrum des Seedpixels betrachtet (Trigger Cluster-25<240 ADC). Es sind nur Einträge bei niedrigen Werten vorhanden. Diese können mit Substratetreffern identifiziert werden. Ein Teil ihrer Ladung rekombiniert im Substrate, die Gesamtladung des Cluster ist damit kleiner als die Triggerbedingung. \newline
 Damit stammen die akzeptierten Cluster aus dem Kalibrations- und Sammelpeak, die verworfenen Cluster aus dem Substratepeak. Denn hier gingen Signalelektronen durch Rekombinationen im Substrate verloren, während in einem unbestrahlten Sensor nahezu alle in der Epitaxieschicht generierten Elektronen gesammelt werden. Damit kann durch diesen Trigger auf Cluster mit einer wohldefinierten Gesamtladung getriggert werden. \newline
 Allerdings ist dieser Trigger nicht mehr anwendbar auf Messungen mit Sensoren, die nicht-ionisierende Strahlenschäden aufweisen, weil hier ebenfalls signifikant viele Rekombinationen in der Epitaxieschicht auftreten.  
 \paragraph{Fe-55-Quelle}
 Eine Fe-Quelle emittiert hauptsächlich $K_{\alpha}$-Photonen einer Energie von 5.9keV. Da die Bindungsenergie für ein Elektron-Lochpaar in Silizium 3.6eV beträgt, konvertiert ein $K_{\alpha}$-Photon in 1640 Signalelektronen. Abhängig von der Entfernung wird jeweils ein entsprechender Bruchteil von einer Diode gesammelt. Werden alle Ladungseinträge eines Clusters aufsummiert, sollten, wenn keine Rekombinationen stattfinden, alle 1640 Elektronen gesammelt werden. \newline
-Eine Fe-55-Quelle emittiert noch zusätzlich $K_{\beta}$-Photonen einer Energie von 6.4keV. Diese führen im Ladungsspektrum zu einem zweiten, kleineren Peak bei höheren Einträgen, da entsprechend weniger $K_{\beta}$-Photonen emittiert werden. Diese Photonen konvertieren auch in der Epitaxieschicht und überlagern folglich das Spektrum der $K_{\alpha}$-Photonen, so dass die Ladungssammlungseffienz eher leicht überschätzt wird. Der Beitrag ist allerdings so gering, dass er meistens vernachlässigt werden kann.\newline
-Mit dem zweiten Kalibrationspeak lässt sich allerdings die Kalibrierung überprüfen. 
+Eine Fe-55-Quelle emittiert noch zusätzlich $K_{\beta}$-Photonen einer Energie von 6.4keV. Diese führen im Ladungsspektrum zu einem zweiten, kleineren Peak bei höheren Einträgen, da entsprechend weniger $K_{\beta}$-Photonen emittiert werden. Diese Photonen konvertieren auch in der Epitaxieschicht und überlagern folglich das Spektrum der $K_{\alpha}$-Photonen, so dass die Ladungssammlungseffienz leicht überschätzt wird. Der Beitrag ist allerdings so gering, dass er meistens vernachlässigt werden kann.\newline
+Allerdings lässt sich mit dem zweiten Kalibrationspeak die Kalibrierung überprüfen. 
 \paragraph{Cd-109-Quelle}
-$K_{\alpha}$-Photonen einer Cd-109-Quelle haben im Vergleich zur Fe-55-Quelle aufgrund der höheren Ordnungszahl von Cd-109 eine viermal höhere Energie von 22keV. Photonen einer Cd-109 sind damit energiereicher und erzeugen höhere Ladungseinträge. In \cite{DoeringMaster} wurde festgestellt, dass dies bei Messungen mit einem hohen Rauschen hilfreich sein kann.\newline
+$K_{\alpha}$-Photonen einer Cd-109-Quelle haben im Vergleich zur Fe-55-Quelle aufgrund der höheren Ordnungszahl von Cd-109 eine viermal höhere Energie von 22keV. Photonen einer Cd-109 erzeugen damit größere Ladungseinträge. In \cite{DoeringMaster} wurde festgestellt, dass dies bei Messungen mit einem hohen Rauschen hilfreich sein kann.\newline
 Weiterhin reicht die Energie eines Cd-109-Photons aus Elektronen aus anderen Materialien herauszuschlagen und dadurch Röntgenfluoreszenzphotonen zu erzeugen. Diese werden als charakteristische Peaks im Spektrum sichtbar, mit denen einerseits die Kalibrierung überprüft werden kann, andererseits sogar eine Materialanalyse ermöglichen. \newline  
  
 \subsubsection{Beta-Quelle}
@@ -426,13 +428,15 @@ Eine $\beta$-Quelle emittiert Elektronen, die den Sensor durchqueren und dabei e
 \paragraph{Ru-106-Quelle}
 Ru-106 zerfällt mit einer Halbwertszeit von 373 Tagen zu Rh-106, welches ebenfalls mit einer Halbwertszeit von 30 Sekunden zerfällt und dabei ein Elektron mit einer Peakenergie von $3,6~\rm MeV$ aussendet. 
 \paragraph{Sr-90-Quelle}
-Sr-90 zerfällt mit einer Halbwertszeit von 28,78 Jahren zu Y-90, welches ebenfalls mit einer Halbwertszeit von 64 Stunden zerfällt und dabei ein Elektron mit einer Peakenergie von $2,2~\rm MeV$ aussendet. Die Energie der ausgesendeten Elektronen ist damit um $40\%$ geringer. Ein direkter Vergleich zwischen Ru-106- und Sr-90-Quelle zeigte aber, dass beide vergleichbare Signale in einem MAPS-Sensor generieren. Sr-90 hat dabei den Vorteil einer längeren Halbwertszeit, so dass die Aktivität der Quelle als konstant angenommen werden kann und nicht regelmäßig ersetzt werden muss. 
+Sr-90 zerfällt mit einer Halbwertszeit von 28,78 Jahren zu Y-90, welches ebenfalls mit einer Halbwertszeit von 64 Stunden zerfällt und dabei ein Elektron mit einer Peakenergie von $2,2~\rm MeV$ aussendet. Die Energie der ausgesendeten Elektronen ist damit um $40\%$ geringer.\newline
+
+Ein direkter Vergleich zwischen Ru-106- und Sr-90-Quelle zeigte aber, dass beide vergleichbare Signale in einem MAPS-Sensor generieren. Sr-90 hat dabei den Vorteil einer längeren Halbwertszeit, so dass die Aktivität der Quelle als konstant angenommen werden kann und nicht regelmäßig ersetzt werden muss. 
 \subsection{Verstärkung}
 \label{kalibrierung}
-Die Verstärkung kann dadurch bestimmt werden, dass in bestimmten Fällen ein Photon ohne Wechselwirkung in der Epitaxieschicht direkt die verarmte Zone der Diode trifft und dort die Signalladung in einem einzigen Pixel freisetzt. Dies erlaubt die Kalibration der Auslesekette unter Ausschluss der Epitaxieschicht und damit die Ermittlung der Verstärkung. Treffer in oder nahe der Diode führen zu einem kleineren, dafür aber sehr schmalen Peak, da die Ladungssammlungseffizienz von $100~\%$ nahe der Diode schnell abfällt und es deshalb im Verhältnis nur kleine Bereiche mit einer hohen Ladungssammlungseffizienz nahe $100\%$ gibt. Der Peak ist der schon vorher angesprochene Kalibrationspeak (calibration peak). Der Kalibrationspeak ist auch in den Spektren mit größerer Clustergröße sichtbar und wird dort zu leicht höheren Signalhöhen verschoben. Zwar enthalten die Nachbarpixel bei einem direkten Diodentreffer keine Signalladung, die Addition benachbarter Pixel mit den jeweils nächstniedrigeren Signalen führt jedoch dazu, dass das Rauschen von Pixel mit einem im Vergleich zu den Nachbarpixel höherem Rauschen zur Signalladung dazugezählt wird. \newline
+Die Verstärkung kann dadurch bestimmt werden, dass in bestimmten Fällen ein Photon ohne Wechselwirkung in der Epitaxieschicht direkt die verarmte Zone der Diode trifft und dort die Signalladung in einem einzigen Pixel freisetzt. Dies erlaubt die Kalibration der Auslesekette unter Ausschluss der Epitaxieschicht und damit die Ermittlung der Verstärkung. Treffer in oder nahe der Diode führen zu einem kleineren, dafür aber sehr schmalen Peak, da die Ladungssammlungseffizienz von $100~\%$ nahe der Diode schnell abfällt und es deshalb im Verhältnis nur kleine Bereiche mit einer hohen Ladungssammlungseffizienz nahe $100\%$ gibt. Der Peak ist der schon vorher angesprochene Kalibrationspeak (calibration peak). Dieser ist auch in den Spektren mit größerer Clustergröße sichtbar und wird dort zu leicht höheren Signalhöhen verschoben. Zwar enthalten die Nachbarpixel bei einem direkten Diodentreffer keine Signalladung, die Addition benachbarter Pixel mit den jeweils nächstniedrigeren Signalen führt jedoch dazu, dass das Rauschen von Pixel mit einem im Vergleich zu den Nachbarpixel höherem Rauschen zur Signalladung dazugezählt wird. \newline
 \subsection{Signal-Rausch-Verhältnis}
 
-Das Signal-Rausch-Verhältnis (signal to noise ratio) gibt an, wie gut ein Signal vom Untergrund unterschieden werden kann. Wie bereits vorher ausgeführt, generiert ein minimal ionisierendes Teilchen Elektronen, die ein Signal im Detektor produzieren. Nun produzieren andere Quellen ebenfalls Elektronen, die als Rauschelektronen das Signal überlagern. Damit erschwert ein kleines Signal und großes Rauschen die Signalidentifikation. Deshalb ist ein großes Signal-Rausch-Verhältnis ein wichtiges Ziel in der Detektorentwicklung.\newline
+Das Signal-Rausch-Verhältnis (signal to noise ratio) gibt an, wie gut ein Signal vom Untergrund unterschieden werden kann. Wie bereits vorher ausgeführt, generiert ein minimal ionisierendes Teilchen Elektronen, die ein Signal im Detektor hervorrufen. Nun generieren andere Quellen ebenfalls Elektronen, die als Rauschelektronen das Signal überlagern. Damit erschwert ein kleines Signal und großes Rauschen die Teilchendetektion. Deshalb ist ein großes Signal-Rausch-Verhältnis ein wichtiges Ziel in der Detektorentwicklung.\newline
 Das Signal-Rausch-Verhältnis evaluiert die Funktionsfähigkeit eines MAPS Chips, da diese die beiden Observablen Rauschen und Ladungssammlungseffizienz in einer zusammenfasst. Geringeres Rauschen und größere Ladungssammlungseffizienz resultieren in einem erhöhten Signal-Rausch-Verhältnis, welches für eine verbesserte Funktionsfähigkeit des MAPS steht.\newline
 Eine Schwerionenkollision produziert hauptsächlich Pionen. Aus diesem Grund wird die durch ein einschlagendes Pion generierte Signalladung als Referenzsignal gewählt um das Signal-Rausch-Verhältnis zu kalibrieren. Pionen stehen in einem Testlabor nicht so einfach zur Verfügung. Aus diesem Grund ist es notwendig Messungen aus Strahltests an Beschleunigern mit Messungen im Labor zu kombinieren.      
 
@@ -440,7 +444,7 @@ Die Grenze zwischen einem intaktem und funktionsunf
 \subsection{Strahltest}
 Ein Strahltest ist der realistischste Test des Sensors. In ihm können vor allem Detektionseffizienzen bestimmt werden. 
 Dazu werden die Spuren zum Beispiel von hochenergetische Pionen mit Hilfe eines Strahlteleskops verwendet. Der zu testende Sensor befindet sich als "`Device under test"' (DUT) innerhalb des Teleskops.\newline
-Nach Rekonstruktion der Spuren kann der Schnittpunkt der Trajektorie mit dem Sensor bestimmt werden. Damit können Teilchenspuren mit Treffern des zu testenden Sensors korreliert werden.\newline 
+Nach Rekonstruktion der Spuren kann der Schnittpunkt der Trajektorien mit dem Sensor bestimmt werden. Damit können Teilchenspuren mit Treffern des zu testenden Sensors korreliert werden.\newline 
 Je nachdem, ob ein Treffer in der Nähe des hypothetischen Schnittpunktes registriert worden ist oder nicht, wird die Detektionseffizienz bestimmt. Die Ortsauflösung des Sensors ergibt sich aus der Distanz des hypothetischen Schnittpunktes mit dem zugeordneten Treffer. \newline
 Zeigt der Sensor einen Treffer an, obwohl keine Spur diesem zugeordnet werden kann, kann ein Fehltreffer identifiziert werden. \newline
   
@@ -451,7 +455,7 @@ In diesem Abschnitt wurde die Extraktion der relevanten Observablen aus dem Prim
 \section{Einfluss des Rauschens}
 Die Erhöhung des Rauschens nach Bestrahlung hat einen starken, nicht immer einfach zu deutenden Effekt auf Strahlenhärteevaluationen. Vereinfacht gesagt erschwert ein zu hohes Rauschen die Signalidentifikation. Dies soll im Folgenden ausdifferenziert werden.
 \subsection{Einfluss des Rauschens auf das Ladungsspektrum}
-Das Rauschen beeinflusst nicht die Signalsammlung in der Epitaxieschicht. Es überlagert sich aber dann in der Auslesekette, so dass trotzdem zu Änderungen im Ladungsspektrum kommt, die leicht mit Rekombinationen mit bestrahlungsinduzierten Defekten missdeutet werden können, die aber ihre Ursache im zu hohen Rauschen haben, was im Folgenden bewiesen werden soll.  
+Das Rauschen beeinflusst nicht die Signalsammlung in der Epitaxieschicht. Es überlagert sich aber dann in der Auslesekette, so dass es trotzdem zu Änderungen im Ladungsspektrum kommt, die leicht mit Rekombinationen mit bestrahlungsinduzierten Defekten missdeutet werden können, die aber ihre Ursache im zu hohen Rauschen haben, was im Folgenden bewiesen werden soll.  
 \begin{figure} 
 \centering 
       
@@ -464,7 +468,7 @@ Das Rauschen beeinflusst nicht die Signalsammlung in der Epitaxieschicht. Es 
 \begin{figure}
 \centering
                \includegraphics[width=1\textwidth]{BilderHR/Mi18SpektrumIrr.pdf}
-               \caption[Ladungsspektrum eines bestrahlten MIMOSA-18-AHR bis $3\cdot 10^{14}~\rm n_{eq}/cm^2$]{Das Ladungsspektrum eines bestrahlten MIMOSA-18-AHR bis zu einer Dosis von $3\cdot 10^{14}~\rm n_{eq}/cm^2$. Während das Spektrum sich bis zu einer Dosis von $3\cdot 10^{13}~\rm n_{eq}/cm^2$ nur leicht ändert, wandelt es sich für die höheren Dosen komplett. Signale sowohl mit hoher als auch niedriger Amplitude verschwinden.}
+               \caption[Ladungsspektrum eines bestrahlten MIMOSA-18-AHR bis $3\cdot 10^{14}~\rm n_{eq}/cm^2$]{Das Ladungsspektrum eines bestrahlten MIMOSA-18-AHR bis zu einer Dosis von $3\cdot 10^{14}~\rm n_{eq}/cm^2$.}
        \label{fig:Mi18SpektrumIrr2}
 \end{figure} 
 Beispielsweise wurden bei MIMOSA-18-AHR-Chips ein sehr hohes Rauschen nach der Bestrahlung mit Neutronen festgestellt (Abbildung \ref{fig:Mi18-high-noise}). Dieses beträgt insbesondere für die höchsten Bestrahlungsdosen von $10^{14}~\rm n_{eq}/cm^2$ und $3\cdot 10^{14}~\rm n_{eq}/cm^2$ über $35~\rm e$.  Abbildung \ref{fig:Mi18SpektrumIrr2} zeigt das dazugehörige Fe-55-Spektrum. Es zeigt sich eine große Änderung des Spektrums nach einer Bestrahlung von $10^{14}~\rm n_{eq}/cm^2$, wo das Rauschen über $35~\rm e$ beträgt. Es verschwinden die Signale sowohl mit niedriger als auch hoher Amplitude. Die obige Frage war, ob dies auf einen Strahlenschaden in der Epitaxieschicht oder auf ein zu hohes Rauschen zurückzuführen ist. \newline
@@ -474,7 +478,7 @@ Dies wird in Abbildung \ref{fig:Mi18-Ru-spektrum2} f
 \begin{figure}
 \centering
                \includegraphics[width=1\textwidth]{BilderHR/Mi18-Ru-spektrum.pdf}
-               \caption[Ru-106-Spektrum eines bestrahlten MIMOSA-18-AHR bis $1\cdot 10^{14}~\rm n_{eq}/cm^2$]{Das Ru-106-Spektrum eines bestrahlten MIMOSA-18-AHR bis zu einer Dosis von $1\cdot 10^{14}~\rm n_{eq}/cm^2$. Bis $3\cdot 10^{13}~\rm n_{eq}/cm^2$ sind die $\beta$ der Ru-Quelle gut vom Rauschen zu trennen (schwarz/rot). Das Signal-Rausch-Verhältnis beträgt für den unbestrahlten Sensor 56 und selbst für den mit $3\cdot 10^{13}~\rm n_{eq}/cm^2$ bestrahlten Sensor 35. Nach $ 10^{14}~\rm n_{eq}/cm^2$ (blau) wird das Spektrum allerdings von Fehltreffern dominiert, wie eine Referenzmessung ohne Quelle (grau) zeigt.}
+               \caption[Ru-106-Spektrum eines bestrahlten MIMOSA-18-AHR bis $1\cdot 10^{14}~\rm n_{eq}/cm^2$]{Das Ru-106-Spektrum eines bestrahlten MIMOSA-18-AHR bis zu einer Dosis von $1\cdot 10^{14}~\rm n_{eq}/cm^2$. Bis $3\cdot 10^{13}~\rm n_{eq}/cm^2$ sind die $\beta$ der Ru-Quelle gut vom Rauschen zu trennen (schwarz/rot). Nach $ 10^{14}~\rm n_{eq}/cm^2$ (blau) wird das Spektrum allerdings von Fehltreffern dominiert, wie eine Referenzmessung ohne Quelle (grau) zeigt.}
        \label{fig:Mi18-Ru-spektrum2}
 \end{figure} 
 Bis zu einer Bestrahlungsdosis von $3\cdot 10^{13}~\rm n_{eq}/cm^2$ ist die Landauverteilung des Ru-Spektrums gut identifizierbar. Wie bereits von den Messungen mit einer Fe-55-Quelle festgestellt, ändert sich das Spektrum nach einer Bestrahlung mit $10^{14}~\rm n_{eq}/cm^2$ allerdings vollständig. Die Anzahl der nachgewiesenen Treffer nimmt stark zu. Die Frage ist, ob diese von der Ru-Quelle stammen oder Fehltreffer aufgrund des stark erhöhten Rauschens sind. Eine Messung ohne die Ru-Quelle gibt einen ersten Hinweis. In dieser Messung sollten keine Teilchen\footnote{Teilchen aus der kosmischen Strahlung werden als vernachlässigbar angenommen.} nachweisbar sein. Angezeigte Treffer können somit auf Fehltreffer zurückgeführt werden. Und in der Tat gibt es einen substantiellen Beitrag von Fehltreffern, der wahrscheinlich das Ru-Spektrum überlagert. Ein unterdrücktes Rauschen könnte den Beitrag der Fehltreffer unterdrücken, so dass diese sich wieder von Treffer der Ru-Quelle trennen lassen sollten.\newline
@@ -489,7 +493,7 @@ Bis zu einer Bestrahlungsdosis von $3\cdot 10^{13}~\rm n_{eq}/cm^2$ ist die Land
  
 \end{figure}
 Die thermische Ausheilung kann das Rauschen nach \cite{DoeringMaster} verringern. Die Frage ist, ob das Rauschen sich soweit verringert lässt, dass der Sensor wieder funktionsfähig wird. 
-Für die Ausheilung nicht-ionisierender Strahlenschäden zeigen die Messergebnisse in Abbildung \ref{fig:Mi18-annealing}, dass sich das Rauschen eines mit Neutronen bestrahlten Sensor nicht verringern lässt. Selbst nach 10 Tagen bei $T=80~{}^{\circ}\rm C$ wurde keine signifikante Änderung des Rauschens festgestellt. Es ist also nicht möglich, das hohe Rauschen eines mit Neutronen bestrahlten MIMOSA-18AHR durch thermische Ausheilung zu verringern. \newline
+Für die Ausheilung nicht-ionisierender Strahlenschäden zeigen die Messergebnisse in Abbildung \ref{fig:Mi18-annealing}, dass sich das Rauschen eines mit Neutronen bestrahlten Sensor nicht verringern lässt. Selbst nach zehn Tagen bei $T=80~{}^{\circ}\rm C$ wurde keine signifikante Änderung des Rauschens festgestellt. Es ist also nicht möglich, das hohe Rauschen eines mit Neutronen bestrahlten MIMOSA-18AHR durch thermische Ausheilung zu verringern. \newline
 \begin{figure} 
 \centering 
      \subfloat[xxx] {\includegraphics[viewport = 50 0 700 550, width=0.5\textwidth] {BilderHR/Mi18-gamma-spektrum-nocool.pdf}}
@@ -525,7 +529,7 @@ F
      \label{fig:Mi18-deepcool-spektrum}  
  
 \end{figure} 
-Zuerst soll wieder das Fe-Spektrum eines unbestrahlten Chips zur Kontrolle betrachtet werden (Abbildung \ref{fig:Mi18-deepcool-spektrum} links). Das Spektrum ändert sich auch bei tieferer Temperatur nicht. Besonderes Augenmerk soll auf den Kalibrationspeak gelegt werden. Änderungen in der Verstärkung wirken sich auf diesen auf. Umgekehrt argumentiert bedeutet der sich nicht ändernde Kalibrationspeak eine temperaturunabhängige Verstärkung. Dies zu prüfen ist unbedingt erforderlich, da die elektronischen Bauteile bei $T=-35~{}^{\circ}\rm C$ außerhalb ihres vorgesehenen Temperaturbereichs betrieben werden. Wird auch das sich nicht ändernde Rauschen berücksichtigt, kann damit für unbestrahlte MAPS in dem betrachteten Temperaturbereich eine temperaturunabhängige Leistungsfähigkeit festgestellt werden.\newline
+Zuerst soll wieder das Fe-Spektrum eines unbestrahlten Chips zur Kontrolle betrachtet werden (Abbildung \ref{fig:Mi18-deepcool-spektrum} links). Das Spektrum ändert sich auch bei tieferer Temperatur nicht. Besonderes Augenmerk soll auf den Kalibrationspeak gelegt werden. Änderungen in der Verstärkung wirken sich auf diesen auf. Umgekehrt argumentiert bedeutet der konstante Kalibrationspeak eine temperaturunabhängige Verstärkung. Dies zu prüfen ist unbedingt erforderlich, da die elektronischen Bauteile bei $T=-35~{}^{\circ}\rm C$ außerhalb ihres vorgesehenen Temperaturbereichs betrieben werden. Wird auch das konstante Rauschen berücksichtigt, kann damit für unbestrahlte MAPS in dem betrachteten Temperaturbereich eine temperaturunabhängige Leistungsfähigkeit festgestellt werden.\newline
 Abbildung \ref{fig:Mi18-deepcool-spektrum} rechts zeigt nun das Fe-Spektrum eines mit $10^{14}~\rm n_{eq}/cm^2$ bestrahlten Sensors. Es werden mit sinkender Temperatur große Änderungen sichtbar. Mit tieferer Temperatur wird wieder der Kalibrationspeak sichtbar, welcher bei $T=-35~{}^{\circ}\rm C$ sogar so groß wie der unbestrahlte Sensor zu sein scheint. \newline
 \begin{figure}
 \centering
@@ -552,18 +556,18 @@ Diese Beobachtungen best
       
    \includegraphics[width=1\textwidth] {Bilder2/Mi18-gamma-neutron-anneal2.pdf} 
      
-     \caption[Vergleich des Rauschens von Neutronen und Gamma bestrahlten Chips mit nur mit Gamma bestrahlten Chips als Funktion der Ausheilzeit]{Vergleich des Rauschens von Neutronen und Gamma bestrahlten Chips mit nur mit Gamma bestrahlten Chips als Funktion der Ausheilzeit bei $T=+80~{}^{\circ}\rm C$. Das Rauschen des Neutronen und Gamma bestrahlten Chips verringert sich trotz der Ausheilung nicht stark signifikant, während sich das Rauschen des nur mit Gammas bestrahlten Sensors halbiert. Die zwei Datenpunkte bei $300~\rm min$ und $700~\rm min$ des Gammabestrahlten Sensors haben ein zu hohes Rauschen. Die naheliegenste Erklärung wäre ein Fehler in der Temperaturkontrolle. Um dies zu prüfen, sollte die Messserie noch einmal wiederholt werden. }  
+     \caption[Vergleich des Rauschens von Neutronen und Gamma bestrahlten Chips mit nur mit Gamma bestrahlten Chips als Funktion der Ausheilzeit]{Vergleich des Rauschens von Neutronen und Gamma bestrahlten Chips mit nur mit Gamma bestrahlten Chips als Funktion der Ausheilzeit bei $T=+80~{}^{\circ}\rm C$.  }  
      \label{fig:Mi18-gamma-neutron-anneal}  
  
 \end{figure}
-Um die Strahlenhärte zu studieren, wird versucht die Mechanismen Oberflächen- und Volumenschäden zu trennen. Oberflächenschäden werden mit weichen Röntgenstrahlen erzeugt. Diese können Atome ionisieren, aber ihr Impuls reicht nicht aus die Atome im Kristallvolumen zu verlagern. Damit tritt kein Volumenschaden auf. Volumenschäden werden mit schnellen Reaktorneutronen erzeugt. Die ungeladenen Neutronen ionisieren kaum Siliziumatome und erzeugen damit keinen Oberflächenschaden.\newline 
+Um die Strahlenhärte zu studieren, wird versucht die Mechanismen von Oberflächen- und Volumenschäden zu trennen. Oberflächenschäden werden mit weichen Röntgenstrahlen erzeugt. Diese können Atome ionisieren, aber ihr Impuls reicht nicht aus die Atome im Kristallvolumen zu verlagern. Damit tritt kein Volumenschaden auf. Volumenschäden werden mit schnellen Reaktorneutronen erzeugt. Die ungeladenen Neutronen ionisieren kaum Siliziumatome und erzeugen damit keinen Oberflächenschaden.\newline 
 Reale Neutronenquellen emittieren allerdings auch Gammastrahlen, die Oberflächenschäden generieren. Man schätzt diesen Anteil auf $\lesssim 100~\rm kRad~pro~10^{13}~\rm n_{eq}/cm^2$. Bei den bisher verwendeten Dosen von $\approx 10^{12}~\rm n_{eq}/cm^2$ wurde die Gamma-Dosis ($\lesssim 10~\rm kRad$) vernachlässigt, sofern der Chip beim Bestrahlen ausgeschaltet blieb. Hochohmige Sensoren erreichen allerdings nun eine Leistungsfähigkeit, die eventuell einen zuverlässigen Betrieb trotz einer Bestrahlungsdosis von mehreren $\approx 10^{14}~\rm n_{eq}/cm^2$ erlauben könnte. Um dies zu evaluieren, sollen die hochohmigen Chips mit schnellen Reaktorneutronen bis zur entsprechend hohen Dosis bestrahlt werden. Die begleitende parasitäre Gammadosis erreicht damit allerdings auch eine Größenordnung von mehreren MRad.\newline
-Die bisher strahlenhärtesten MAPS gegenüber ionisierende Strahlung, optimierte MIMOSA-11, erreichen ebenfalls gerade einmal 3MRad \cite{Devxraypaper}. Dies allerdings bei betriebenen Sensoren. Dies macht einen Unterschied, denn Oberflächenschäden entstehen unter anderem dadurch, dass Strahlung im SiO2 Elektronen ins Leitungsband hebt. Elektrische Felder saugen die Elektronen ab, die Löcher bleiben als metastabiler Defekt zurück.  Sofern keine elektrischen Felder angelegt sind (Chip ausgeschaltet), rekombinieren diese Elektronen oft wieder mit ihrem Loch. Hierdurch wird die Ausbildung von Oberflächenschäden stark unterdrückt.\newline 
+Die bisher strahlenhärtesten MAPS gegenüber ionisierende Strahlung, optimierte MIMOSA-11, erreichen ebenfalls gerade einmal 3MRad \cite{Devxraypaper}. Dies allerdings bei betriebenen Sensoren. Dies macht einen Unterschied, denn Oberflächenschäden entstehen unter anderem dadurch, dass Strahlung im SiO2 Elektronen ins Leitungsband hebt. Elektrische Felder ziehen die Elektronen ab, die Löcher bleiben als metastabiler Defekt zurück.  Sofern keine elektrischen Felder angelegt sind (Chip ausgeschaltet), rekombinieren diese Elektronen oft wieder mit ihrem Lochpartner. Hierdurch wird die Ausbildung von Oberflächenschäden stark unterdrückt.\newline 
 Ein strahlenhartes Design gegenüber ionisierende Strahlenschäden kann durch spezielle, geschützte Transistoren erreicht werden. Das Design kann die Ausbildung von leitenden Kanälen durch Bestrahlung verhindern. Diese benötigen allerdings ein aufwändigeres Design, was in den speziell für ionisierende Strahlenhärte optimierten MIMOSA-11, die über einen teilweise größeren Pixelpitch verfügen, verwirklicht wurde, in MIMOSA-18AHR, einem Chip zur Evaluierung der nicht-ionisierenden Strahlenhärte, noch nicht.\newline
 Es gibt also mehrere Aspekte abzuwägen. Die ionisierenden Strahlenschädeneffekte sollten in MIMOSA-18AHR geringer sein, weil die Chips während der Bestrahlung ausgeschaltet waren. Sie könnten allerdings auch größer sein, weil das Design von MIMOSA-18AHR nicht strahlenhart ausgelegt war.\newline 
 Nichtsdestotrotz ist das eigentliche Ziel von MIMOSA-18AHR die Grenzen der nicht-ionisierenden Strahlenhärte von hochohmigen Sensoren zu evaluieren. Deshalb sollte sichergestellt werden, dass auch wirklich die Effekte der nicht-ionisierenden Strahlung und nicht fälschlicherweise die der begleitenden parasitären ionisierenden Strahlung untersucht werden. \newline
 \subsection{Vergleich mit Co-60-bestrahlten Sensoren}
-Zu diesem Zweck wurden MIMOSA-18AHR mit Gammastrahlung einer Co-60-Quelle bestrahlt ZITAT. Die Chips waren während der Bestrahlung genauso wie bei der Reaktorbestrahlung nicht gebondet. Eine Co-60-Quelle anstatt einer Röntgenquelle wurde gewählt, um die Gammabestrahlung möglichst bei vergleichbaren Gammaenergien durchzuführen. Dadurch wurde die Annahme einer energieunabhängigen ionisierenden Strahlendosis vermieden. \newline
+Zu diesem Zweck wurden MIMOSA-18AHR mit Gammastrahlung einer Co-60-Quelle bestrahlt ZITAT. Die Chips waren während der Bestrahlung wie bei der Reaktorbestrahlung nicht gebondet. Anstatt einer Röntgenquelle wurde eine Co-60-Quelle gewählt, um die Gammabestrahlung möglichst bei vergleichbaren Gammaenergien durchzuführen. Dadurch wurde die Annahme einer energieunabhängigen ionisierenden Strahlendosis vermieden. \newline
 Die Idee ist die Dosis so zu wählen, dass sie äquivalent zu der abgeschätzten parasitären Dosis während der Reaktorbestrahlung ist, und somit durch Vergleich die verschiedenen Anteile zu extrahieren.\newline 
 Erwartet wurde, eine vergleichbare Dosimetrie vorausgesetzt, dass das Rauschen des Reaktorbestrahlten Chips ungefähr gleich oder höher ist als das der Co-60-bestrahlten Chips. Denn die Reaktorbestrahlten Chips haben nicht nur die das Rauschen erhöhende Gammadosis erhalten, sondern zusätzlich auch eine Bestrahlung durch Neutronen, die ebenfalls das Rauschen erhöhen. Unklar war, wie stark das Rauschen der Co-60-bestrahlten Chips nach der Bestrahlung ist. Eine vernachlässigbare Erhöhung des Rauschens aufgrund der bei der Bestrahlung ausgeschalteten Sensoren war ebenso denkbar wie ein Rauschen, das mit denen der Reaktorbestrahlten Chips vergleichbar ist, weil der Anstieg des Rauschens dominierend auf ionisierende Strahlenschäden zurückzuführen ist. Ein drittes Argument ist die thermische Ausheilung bei Raumtemperatur, die das Rauschen aufgrund der ionisierenden Bestrahlung bereits auf ein im Vergleich zum Rauschen der nicht-ionisierenden Strahlenschäden vernachlässigbaren Wert vermindert haben könnte.\newline   
 Abbildung \ref{fig:Mi18-gamma-neutron-noise} zeigt die Ergebnisse. Das Rauschen des Gammabestrahlten Chips steigt mit der Bestrahlungsdosis an auf bis zu $35~\rm e$. Damit kann als allererstes festgestellt werden, dass das Rauschen aufgrund ionisierender Strahlenschäden bei Bestrahlungsdosen bis 3 MRad nicht vernachlässigbar klein ist.\newline