Transcript silicons talk

Substitution Structures of Multiple Silicon-Containing Species
by Chirped Pulse FTMW Spectroscopy
Nathan A. Seifert, Simon Lobsiger, Brooks H. Pate
University of Virginia
Gamil A. Guirgis, Jason S. Overby
College of Charleston
James. R. Durig
University of Missouri, Kansas City
Introduction
Goal: Using CP-FTMW spectroscopy to assign a standard molecular structure
with minimal sample usage and ~1 day of experimental effort
Motivating question: How can we make the process of spectral fitting in MW spectroscopy
efficient and easy, so the technique is available to even those not trained in rotational spectroscopy?
To solve this, we have developed:
Autofit – Automated triples fitter
(Front end for SPCAT/SPFIT1)
(see additionally Steber et al., TC10 2010; Shipman, et al., RH01 2011)
(Steve Shipman of New College of Florida and Ian Finneran of Caltech did most of the programming work, so our eternal gratitude to them!)
Anecdote: On a good day, a Pate lab group member can check a given
triple for goodness of fit once every two to three minutes using JB95.
Every day, Autofit can fit approximately >250 triples in a single second.
Fitting a rigid rotor spectra is a purely mechanical task,
so why not automate it? The beauty in
rotational spectroscopy, after all, is in the analysis.
1. H. M. Pickett, J. Mol. Spectrosc., 148 (1991), 371.
Autofit Program Flow
Enter guess
rotational constants &
dipole moments (ab initio
predictions)
SPCAT
Choose three
transitions to fit
INPUT STAGE
No
Are transitions
sufficiently linearly
independent to fit
A, B & C?
CHOICE STAGE
Input window size Δν:
For checking triples
with expt. freqs within
±Δν
Input two column peakpick
of target broadband
spectrum
M cores
Split full triples lists into
M subarrays
Yes
Choose N
additional transitions
for checking fit
correctness
PROCESS STAGE
M SPFIT
instances
Fit each A/B/C triple
with N + 3 transitions
Sort triples fits
by OMC,
collate & output
Technical features:
•
•
Written in Python; works on any platform with a Python interpreter
•
Only requires compatible SPCAT/SPFIT binaries
Easily scalable to multiple CPU cores
Autofit Benchmarking
CPU used: Intel Core i7-3770S
(3.1 GHz / 3.9 GHz turbo)
• 4 physical cores
(8 logical w/ hyperthreading)
• 8MB L3 cache, 4 x 256KB L2 cache
• $300 on newegg.com (as of May 2013)
Some performance observations:
• Invariant to RAM availability
• Strong dependence on CPU
cache & cache bandwidth
Optimal performance would
likely be found using a high
performance CPU with a good
cache, like the Intel Xeon or
AMD Opteron series
Motivating Examples
5 molecules chosen – in collaboration with Gamil Guirgis of College of Charleston:
(results also available for 1-isocyanatosilyl-cyclopropane)
CH3SiHFNCO
1-cyanosilyl-cyclopropane
1,1,3,3-tetra(fluoro/hydro)-1,3-disilacyclopentane
1-isocyanato-1-silacyclohexane
In all cases, a single Autofit run detected the parent species
as well as all isotopologues detectable in natural abundance
Autofit philosophy:
•
Initial guess rotational constants/dipoles from MP2/6-311++g(d,p) structures
• Chose the 3 fit transitions from typical strong features that can fit A, B & C well
• 5-7 additional strong transitions for checking fit, typically between 7-12 GHz
• Peakpick cutoff made to include all lines ca. >4:1 signal to noise ratio
• ~500 MHz window for all autofit runs
• CP-FTMW spectra for all systems taken with the new upgrades
at 6.5-18 GHz (Similar to 2-8 GHz improvements seen in the slides of Cristobal’s talk, TH10).
• Spectra range from 120k to 500k averages (one afternoon max. of averaging)
CH3SiHFNCO – Autofit Results
120,000 avg. spectrum (1 hr)
Top 16 fits from Autofit output:
A (MHz)
B (MHz)
C (MHz)
OMC (kHz)
Assignment
6427.20
1585.675
1265.95
27.7
No match
6150.49
1516.959
1291.71
28.2
13CH
3
6298.88
1518.946
1299.04
31.6
N13CO
6277.93
1527.439
1305.77
33.8
30Si
6217.09
1534.432
1311.16
35.2
NS
6288.59
1536.618
1330.514
36.3
No match
6294.44
1554.153
1274.29
37.7
No match
6257.27
1534.867
1310.90
37.8
NS
6300.71
1534.827
1310.89
38.8
NS
6295.23
1529.44
1308.519
38.8
29Si
6427.03
1585.684
1265.95
42.7
No match
6248.73
1517.939
1300.05
44.5
N13CO
6294.93
1535.399
1310.27
45.0
NS
6441.8
1600.815
1241.58
45.2
No match
6294.33
1533.594
1308.77
45.5
15N
6294.77
1533.987
1308.88
45.9
15N
(rough)
• 6.14 million triples (7 hrs, 8 cores)
Fit transitions:
• One a-type Ka = 0 (B+C)
• Two b-type transitions (A; asymmetry)
Note:
• OMCs unusually high due
to A/E splitting and
hyperfine
CH3SiHFNCO – Final Results
•
A/E states + quad fit simultaneously with XIAM
•
Structural trends consistent with CH3SiF2NCO results (2012 MH08)
• V3 decreases with additional halogenation; r[H3C-Si] decreases by 0.3 Å
• Difluoro V3: 446(5) cm-1; CH3SiF2Cl V3: 463(3) cm-1
• Similar bend in –NCO: <[Si-N-C] = 159.8(9)° (F2); 152.6(18)° (HF)
Parent Species Results
MP26-
Expt.
311++g(d,p)
MP2/6-311++g(d,p) structure
overlaying rs coordinates
Isotopologue Results (Other parameters held fixed)
29Si
30Si
13CH
3
N13CO
15N
A (MHz)
6290.281(46)
6279.457(60)
6159.135(51)
6299.287(50)
6295.336(28)
B (MHz)
1530.6263(68) 1526.2869(11) 1516.9197(43) 1518.6229(42) 1532.7715(44)
C (MHz)
1307.7311(61) 1305.0436(10) 1291.7792(37) 1298.4160(35) 1308.5262(38)
Nlines
64
57
22
24
20
σfit (kHz)
20.3
20.8
17.9
21.4
19.6
A (MHz)
6086.35
6301.415(45)
B (MHz)
1524.42
1535.078(39)
C (MHz)
1304.04
1310.485(39)
ΔJ (kHz)
0.606
0.742(33)
ΔJK (kHz)
101.01
41.50(14)
ΔK (kHz)
-115.14
-25.39(10)
δJ (kHz)
0.034
0.067(13)
δK (kHz)
69.19
25.6(19)
3/2 χaa
(MHz)
3.27
2.655(11)
¼(χbb-χcc)
(MHz)
46.36
23(18)
V3 (cm-1)
436
480(19)
F (GHz)
[158]
155.7(66)
θ (deg)
57.6
58.6(10)
Nlines
--
150
σfit (kHz)
--
18.9
1-isocyanato-1-silacyclohexane – Autofit Results
320,000 avg. spectrum (2.8 hrs)
Axial-, selected Autofit results (with sorted rankings)
Rank
A (MHz)
B (MHz)
C (MHz)
OMC (kHz)
Assignment
1
1942.32
951.832
923.025
15.2
15N
2
1953.55
954.585
926.465
20.8
NS
4
1936.75
954.847
924.089
21.2
29Si
6
1952.15
945.318
917.625
21.4
13C-2
8
1935.21
949.289
921.503
22.2
13C-4
9
1921.58
955.012
921.342
23.1
30Si
12
1934.06
948.689
922.151
24.8
13C-3
15
1936.25
946.925
916.908
26.5
13CN
Axial
ΔE = 0 cm-1
• 6.13 million triples (10 hrs, 4 cores)
Fit transitions:
• Three a-types; Ka = 0, Ka = 1, Ka = 2
Little A dependence, so error on A is
high
Equa-, selected Autofit results (with sorted rankings)
Rank
A (MHz)
B (MHz)
C (MHz)
OMC (kHz)
1
3441.4
690.101
608.989
7.6
NS
Assignment
2
3438.2
689.609
608.981
11.9
30Si
4
3432.5
689.845
608.972
17.6
29Si
5
3450.2
682.162
602.817
18.3
13CN
7
3427.6
682.189
603.121
19.0
13C-4
10
3370.2
689.485
606.833
20.9
13C-2
12
3412.9
685.212
603.925
21.6
13C-3
13
3410.3
687.168
606.641
23.4
15N
• 5.03 million triples (~9 hrs, 4 cores)
Fit transitions:
• Three a-types; Ka = 0, Ka = 1, Ka = 2
Equatorial
ΔE = 414 cm-1
1-isocyanato-1-silacyclohexane – Results
Open issue:
MP2 (as well as DFT)
Severely underestimates NCO bending
angle (Xaa discrepencies are a real tell!)
MP2
6-311++g(d,p)
Expt.
MP2
6-311++g(d,p)
Expt.
A (MHz)
2261.9804
1949.06(44)
A (MHz)
3530.4152
3440.37(26)
B (MHz)
808.24933
954.8421(20)
B (MHz)
686.04800
690.1025(18)
C (MHz)
779.80522
926.7693(17)
C (MHz)
606.12607
608.9931(18)
ΔJ (kHz)
--
1.6593(94)
ΔJ (kHz)
--
0.0910(61)
ΔJK (kHz)
--
-2.767(45)
ΔJK (kHz)
--
8.076(52)
ΔK (kHz)
--
1597(155)
ΔK (kHz)
--
[0]
δJ (kHz)
--
-0.328(82)
δJ (kHz)
--
[0]
δK (kHz)
--
[0]
δK (kHz)
--
2.92(80)
3/2 χaa (MHz)
2.10
0.941(33)
3/2 χaa (MHz)
3.03
2.461(80)
¼(χbb-χcc)
(MHz)
-0.153
0.276(13)
¼(χbb-χcc)
(MHz)
[0]
[0]
Nlines
--
66
Nlines
--
123
σfit (kHz)
--
14.6
σfit (kHz)
--
16.4
Conclusions
Autofit is a fast and efficient way to quickly assign broadband spectra
for both parent species and isotopologues for the purpose of molecular
identification or structural determination.
Orders of magnitude faster than routine, manual spectra fitting
Helps enable structure determination via CP-FTMW become a
routine activity
With new CP-FTMW spectra approaching line densities of over >1
MHz-1, visual pattern recognition for weakly abundant species is
nearly impossible
•
•
•
The Future of Autofit:
•
•
Automated optimization for choosing a frequency window size with respect to typical ab initio error on A/B/C
Automated choosing of 3 fit transitions based on optimal linear independence to fit A/B/C
•
A graphical interface where autofit results are integrated into a JB95/PGOPHER/AABS-like interactive fitting program
On the technical side:
CPU scaling via the cloud is cheap and perhaps even trivial!
• A quick back of the envelope calculation for large scaling on Amazon EC2 clusters:
• Assume 50 Hz/core; 20 EC2 logical cores/instance for $0.580/hr
• Maximum of 20 instances at once, so 400 logical cores for $11.60/hr
• Effective compute speed of 20 kHz, so 500 seconds to fit 107 triples  $1.60 per autofit run!
Acknowledgements
Shameless plug – Autofit is freely available at http://tinyurl.com/autofitcpftmw
• git repository: git clone git://github.com/pategroup/bband_scripts.git
• Works in Windows, but even easier to setup in x86/x86-64 Linux!
Pate Group
Brooks Pate
Cristobal Perez
Simon Lobsiger
Luca Evangelisti
Brent Harris
Amanda Steber
Nathan Seifert
Thanks for your time!
Thanks to the NSF for funding:
MRI-R2, Award CHE-0960074
CH3SiHFNCO – Final Results
How does it compare to
other species in the series?
Species
V3 (cm-1)
R[H3C-Si] (Å)
Citation
(CH3)2SiH2
576.4
1.867(2)
L. Pierce, J. Chem. Phys. 34 (1961) 498.
CH3SiH2Cl
644
1.849(5)
R. H. Schwendeman, G.D. Jacobs, J. Chem. Phys. 36 (1962)
1251.
CH3SiHCl2
731
--
J. R. Durig, C. W. Hawley, J. Chem. Phys. 59 (1973) 1.
CH3SiCl3
875
1.848
M. A. Qtaitat, et al., Spectrochim. Acta A, 50 (1994) 621.
CH3SiH2F
545(1)
1.849(5)
L.C. Krisher, L. Pierce, J. Chem. Phys. 32 (1960) 1619.
CH3SiHF2
439(10)
1.840(1)
L.C. Krisher, L. Pierce, J. Chem. Phys. 32 (1960) 1619.
CH3SiF3
413.994(9)
1.812(14)
J.R. Durig, Y.S. Li, C.C. Tong, J. Mol. Struct. 14 (1972) 255.
CH3SiF2NCO
446(5)
1.814(5)
G.A. Guirgis, et al. J. Phys. Chem. A. 116 (2012) 7822.
CH3SiF2Cl
468(3)
1.814(1)
N. A. Seifert, et al. J. Mol. Struct. 1023 (2012) 222.
CH3SiHFNCO
480(19)
1.843(7)
This work