aboutsummaryrefslogtreecommitdiff
path: root/presentation.tex
blob: 9f4a3f1d3def5aeecd3a4d55ea65463d8eb52e57 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
\documentclass{presentation}

\title{Development of \\ Frequency Domain Multidimensional Spectroscopy}
\author{Blaise Thompson}

\institute{University of Wisconsin--Madison}
\date{2018-04-23}

\begin{document}
\maketitle

\section{CMDS}  % =================================================================================

\begin{frame}{CMDS}
	The Wright Group focuses on the development and usage of \\
  Coherent MultiDimensional Spectroscopy (CMDS).
  \vspace{\baselineskip} \\
  CMDS is a family of related nonlinear spectroscopic experiments.
\end{frame}
   
\begin{frame}{Why CMDS?}
  [A BUNCH OF COOL PUBLICATIONS---FOCUSING ON COHERENCE TRANSFER, MECHANISMS ETC]
  [MORE APPLICATIONS]
\end{frame}

\begin{frame}{Coherence transfer}
  \fbox{\adjincludegraphics[width=\textwidth]{literature/ChenuAurelia2014a}}
\end{frame}

\begin{frame}{Analytical}
  But wait! I'm an \emph{Analytical} Chemist...
  \vspace{\baselineskip} \\
  What am I doing in a field so rich with fundamental studies?
  \vspace{\baselineskip} \\
  I hope to convince you that CMDS can be used for analytical work.  % TODO: better
  \begin{itemize}
    \item detection (selectivity)
    \item unknown identification
    \item quantification
  \end{itemize}
\end{frame}

% TODO: in fact, 2DIR is already used regularly...

\begin{frame}{Pakoulev et al. (2009)}  
  \fbox{\adjincludegraphics[width=\textwidth]{literature/PakoulevAndreiV2009a}}
\end{frame}

\begin{frame}{Pakoulev et al. (2009)}
  \begin{shadequote}
    Spectroscopy forms the heart of the analytical methodology used for routine chemical
    measurement.  %
    Of all the analytical spectroscopic methods, NMR spectroscopy is unique in its ability to
    \hl{correlate} spin resonances and \hl{resolve} spectral features from spectra containing
    \hl{thousands of peaks}.  %
    For example, heteronuclear multiple quantum coherence (HMQC) spectroscopy achieves this
    capability by exciting $^1$H, $^{15}$N, $^{13}$ C=O, and $^{13}$C$\alpha$ spins to form a
    multiple quantum coherence \hl{characteristic of a specific position} in a protein’s backbone.
    Three excitations define a specific residue, and a fourth defines the coupling to an adjacent
    residue.
    Not only does it decongest the spectra, it defines the couplings and connectivity between the
    different nuclear spin states.
    Coherent multidimensional spectroscopy (CMDS) has emerged as the \hl{optical analogue} of
    nuclear magnetic resonance (NMR), and there is great interest in using it as a \hl{general
      analytical methodology}.
  \end{shadequote}
\end{frame}

\begin{frame}{Donaldson et al. (2010)}
  \fbox{\adjincludegraphics[width=\textwidth]{literature/DonaldsonPaulMurray2010a}}
\end{frame}

\begin{frame}{Fournier et al. (2009)}
  \fbox{\adjincludegraphics[width=\textwidth]{literature/FournierFrederic2009a}}
\end{frame}

\begin{frame}{Fournier et al. (2009)}
  \begin{shadequote}
    Our protein identification strategy is based on using EVV 2DIR to quantify the amino acid
    content of a protein.  %
    EVV 2DIR is shown to be able to perform \hl{absolute quantification}, something of major
    importance in the field of proteomics but rather difficult and time-consuming to achieve with
    mass spectrometry.  %
    Our technique can be qualified as a top-down \hl{label-free} method; it does not require
    intensive sample preparation, the proteins are intact when analyzed, and it does not have any
    mass restriction on the proteins to be analyzed.  %
    Moreover, EVV 2DIR is a \hl{nondestructive} technique; the samples can be kept for reanalysis
    in the light of further information.  %
  \end{shadequote}
\end{frame}

\section{Frequency domain}  % =====================================================================

\begin{frame}{Domains of CMDS}
  CMDS can be collected in two domains:
  \begin{itemize}
    \item time domain
    \item frequency domain
  \end{itemize}
\end{frame}

\begin{frame}{Time domain}
  Multiple broadband pulses are scanned in \emph{time} to collect a multidimensional interferogram
  (analogous to FTIR, NMR).
  \vspace{\baselineskip} \\
  A local oscillator must be used to measure the \emph{phase} of the output.
  \vspace{\baselineskip} \\
  This technique is...
  \begin{itemize}
    \item fast (even single shot)
    \item robust
  \end{itemize}
  pulse shapers have made time-domain CMDS (2DIR) almost routine.
\end{frame}

\begin{frame}{Frequency domain}
  In the Wright Group, we focus on \emph{frequency} domain ``Multi-Resonant'' (MR)-CMDS.
  \vspace{\baselineskip} \\
  Automated Optical Parametric Amplifiers (OPAs) are used to produce relatively narrow-band pulses.
  Multidimensional spectra are collected ``directly'' by scanning OPAs against each-other.
  \vspace{\baselineskip} \\
  This strategy is...
  \begin{itemize}
    \item slow (must directly visit each pixel)
    \item fragile (many crucial moving pieces)
  \end{itemize}
  but! It is incredibly flexible.  
\end{frame}

\begin{frame}{Bandwidth}
  MR-CMDS has no bandwidth limit!
  \vspace{\baselineskip} \\
  There is just the small matter of making the source continuously tunable...
  \adjincludegraphics[width=\textwidth]{opa/OPA_ranges}
\end{frame}

\begin{frame}{Selection rules}
  MR-CMDS can easily collect data without an external local oscillator.
  \vspace{\baselineskip} \\
  This means... [BOYLE]
\end{frame}

\section{The instrument}  % =======================================================================

\begin{frame}{The instrument}
  [PICTURE OF LASER LAB]
\end{frame}

\begin{frame}{The instrument}
  Many kinds of component hardware
  \begin{itemize}
    \item monochromators
    \item delay stages
    \item filters
    \item OPAs
  \end{itemize}
  $\sim10$ settable devices, $\sim25$ motors. \\
  Multiple detectors.
\end{frame}

\begin{frame}{Pipeline}
  \adjincludegraphics[width=0.5\textwidth]{presentation/pipe}
  What does the ``pipeline'' of MR-CMDS data acquisition and processing look like in the Wright
  Group?
  \vspace{\baselineskip} \\
  How to increase data throughput and quality, while decreasing frustration of experimentalists?  %
\end{frame}

\section{Processing}  % ===========================================================================

\begin{frame}{Processing}
  WrightTools.
\end{frame}

\begin{frame}{Universal format}
  WrightTools defines a \emph{universal file format} for CMDS.
  \begin{itemize}
    \item store multiple multidimensional arrays
    \item metadata
  \end{itemize}
  Import data from a variety of sources.
  \begin{itemize}
    \item previous Wright Group acquisition software
    \item commercial instruments (JASCO, Shimadzu, Ocean Optics)
  \end{itemize}
\end{frame}

\begin{frame}{Flexible data model}
  Flexibility to transform into any desired ``projection'' on component variables.
  \adjincludegraphics[width=\textwidth]{processing/fringes_transform}
  % mention: including expressions
\end{frame}

\section{Acquisition}  % ==========================================================================

\begin{frame}{Acquisition}
  PyCMDS---unified software for controlling hardware and collecting data.
  \adjincludegraphics[width=\textwidth]{acquisition/screenshots/000}
\end{frame}

\begin{frame}{Abstraction}
  Hardware---something that has a \hl{position} that can be \hl{set}.
  \vspace{\baselineskip} \\
  Sensor---something that has a \hl{signal} that can be \hl{read}.
\end{frame}
  
\begin{frame}{Modular hardware model}
  \adjincludegraphics[scale=0.25]{acquisition/hardware_inheritance}
\end{frame}

\begin{frame}{Modular sensor model}
  Can have as many sensors as needed.
  \vspace{\baselineskip} \\
  Each sensor contributes one or more channels.
  \vspace{\baselineskip} \\
  Sensors with size contribute new variables (dimensions).
\end{frame}

\begin{frame}{Central loop}
  Set, wait, read, wait, repeat.
  \vspace{\baselineskip} \\
  Everything is multi-threaded (simultaneous motion, simultaneous read).
\end{frame}
  
\begin{frame}{Acquisitions}
  Acquisition---a particular set of actions.
  \vspace{\baselineskip} \\
  Acquisition modules---a GUI that accepts a user instruction.
\end{frame}

\begin{frame}{Queue}
  Queue.
  \adjincludegraphics[width=\textwidth]{acquisition/screenshots/004}
\end{frame}

\begin{frame}{Queue}
  This strategy can be incredibly productive!
  \begin{itemize}
    \item Soon after the queue was first implemented, we collected more pixels in two weeks than
      had been collected over the previous three years.
  \end{itemize}
\end{frame}

\section{Tuning}  % ===============================================================================

\begin{frame}{Tuning}
\end{frame}

\section{Conclusion}  % ===========================================================================

\begin{frame}{Conclusion}
\end{frame}

\section{Supplement}  % ===========================================================================

\begin{frame}{MR-CMDS theory}
\end{frame}

\begin{frame}{Mixed domain}
  [FIGURES FROM DAN'S PAPER]
\end{frame}

\end{document}