Fixed carbon nanotube and optimize chain water

We want to fix the nanotube and optimize the chain water in the presence of the nanotube. However, we found some error and slow calculated speed. Thank you very much!
Input file is as follows:
$rem
METHOD M06-2X
DFT_D = D3_ZERO
basis aug-cc-pVTZ
jobtype opt
SCF_ALGORITHM DIIS
THRESH 14
SCF_CONVERGENCE 8
SCF_MAX_CYCLES 100000
MAX_DIIS_CYCLES=1000000
GEOM_OPT_MAX_CYCLES 100000
GEOM_OPT_TOL_DISPLACEMENT=60
GEOM_OPT_TOL_GRADIENT=20
GEOM_OPT_TOL_ENERGY=10
XC_GRID 000099000590
SYM_IGNORE true
SYMMETRY false
MEM_TOTAL = 40000
MEM_STATIC = 4000
$end

$molecule
0 1
C 3.54884820 -0.10909158 -1.64345106
C 3.34801985 -1.31219037 -2.36256322
C 3.54462169 -0.11794722 -0.22248495
C 3.33956681 -1.32990163 0.47936902
C 3.53616865 -0.13565847 2.61944729
C 3.33534029 -1.33875726 1.90033514
C 3.53194213 -0.14451410 4.04041341
C 3.32688725 -1.35646852 4.74226738
C 3.52348909 -0.16222536 6.88234566
C 3.32266074 -1.36532414 6.16323351
C 3.51926257 -0.17108099 8.30331177
C 3.31420770 -1.38303541 9.00516574
C 3.51080954 -0.18879225 11.14524401
C 3.30998119 -1.39189104 10.42613186
C 3.50658302 -0.19764788 12.56621013
C 3.30152815 -1.40960229 13.26806410
C 3.49812998 -0.21535913 15.40814238
C 3.29730163 -1.41845792 14.68903023
C 3.49390346 -0.22421477 16.82910849
C 3.28884859 -1.43616918 17.53096246
C 3.48545043 -0.24192602 19.67104073
C 3.28462208 -1.44502481 18.95192858
C 3.48122391 -0.25078165 21.09200686
C 3.27616904 -1.46273607 21.79386083
C 3.47277088 -0.26849290 23.93393909
C 3.27194252 -1.47159169 23.21482695
C 3.46854436 -0.27734854 25.35490521
C 3.26348948 -1.48930296 26.05675918
C 2.70469712 2.14948855 -1.63188617
C 3.32811481 1.09884919 -2.34759654
C 2.70047060 2.14063291 -0.21092005
C 3.31966177 1.08113794 0.49433570
C 2.69201757 2.12292166 2.63101219
C 3.31543527 1.07228231 1.91530182
C 2.68779105 2.11406603 4.05197831
C 3.30698223 1.05457105 4.75723406
C 2.67933801 2.09635477 6.89391055
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C 2.67511149 2.08749914 8.31487667
C 3.29430267 1.02800416 9.02013242
C 2.66665845 2.06978788 11.15680891
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C 2.66243193 2.06093225 12.57777503
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C 2.65397891 2.04322100 15.41970727
C 3.27739660 0.99258164 14.70399690
C 2.64975239 2.03436536 16.84067339
C 3.26894356 0.97487039 17.54592914
C 2.64129935 2.01665411 19.68260563
C 3.26471704 0.96601476 18.96689526
C 2.63707283 2.00779848 21.10357175
C 3.25626401 0.94830350 21.80882750
C 2.62861979 1.99008723 23.94550399
C 3.25203749 0.93944787 23.22979363
C 2.62439327 1.98123159 25.36647012
C 3.24358445 0.92173661 26.07172586
C 0.60600740 3.33763252 -1.63072386
C 1.76183817 2.93326697 -2.34082296
C 0.60178088 3.32877688 -0.20975773
C 1.75338513 2.91555571 0.50110928
C 0.59332784 3.31106563 2.63217451
C 1.74915861 2.90670009 1.92207540
C 0.58910132 3.30221000 4.05314062
C 1.74070557 2.88898882 4.76400764
C 0.58064829 3.28449874 6.89507287
C 1.73647905 2.88013319 6.18497376
C 0.57642177 3.27564311 8.31603899
C 1.72802602 2.86242194 9.02690600
C 0.56796873 3.25793185 11.15797123
C 1.72379951 2.85356631 10.44787212
C 0.56374221 3.24907622 12.57893734
C 1.71534647 2.83585505 13.28980436
C 0.55528917 3.23136497 15.42086959
C 1.71111995 2.82699942 14.71077048
C 0.55106266 3.22250933 16.84183571
C 1.70266691 2.80928816 17.55270273
C 0.54260963 3.20479808 19.68376794
C 1.69844039 2.80043254 18.97366884
C 0.53838311 3.19594245 21.10473406
C 1.68998735 2.78272127 21.81560108
C 0.52993007 3.17823119 23.94666631
C 1.68576084 2.77386564 23.23656720
C 0.52570355 3.16937556 25.36763243
C 1.67730780 2.75615439 26.07849944
C -1.76580872 2.89860009 -1.64051468
C -0.61671974 3.33154723 -2.34541561
C -1.77003524 2.88974446 -0.21954856
C -0.62517278 3.31383597 0.49651663
C -1.77848827 2.87203320 2.62238368
C -0.62939930 3.30498035 1.91748276
C -1.78271479 2.86317757 4.04334980
C -0.63785234 3.28726908 4.75941499
C -1.79116782 2.84546632 6.88528204
C -0.64207886 3.27841345 6.18038111
C -1.79539434 2.83661069 8.30624816
C -0.65053190 3.26070220 9.02231335
C -1.80384738 2.81889942 11.14818040
C -0.65475841 3.25184657 10.44327948
C -1.80807390 2.81004380 12.56914652
C -0.66321145 3.23413531 13.28521171
C -1.81652694 2.79233254 15.41107876
C -0.66743796 3.22527968 14.70617783
C -1.82075346 2.78347691 16.83204488
C -0.67589100 3.20756842 17.54811008
C -1.82920648 2.76576565 19.67397713
C -0.68011752 3.19871280 18.96907620
C -1.83343300 2.75691002 21.09494324
C -0.68857056 3.18100153 21.81100843
C -1.84188604 2.73919877 23.93687548
C -0.69279707 3.17214590 23.23197455
C -1.84611256 2.73034314 25.35784160
C -0.70125011 3.15443465 26.07390680
C -3.29927297 1.03796624 -1.65667150
C -2.69456186 2.10831765 -2.35921925
C -3.30349949 1.02911061 -0.23570538
C -2.70301490 2.09060638 0.48271299
C -3.31195253 1.01139935 2.60622685
C -2.70724141 2.08175076 1.90367912
C -3.31617905 1.00254372 4.02719297
C -2.71569445 2.06403950 4.74561135
C -3.32463208 0.98483246 6.86912522
C -2.71992097 2.05518387 6.16657747
C -3.32885859 0.97597683 8.29009134
C -2.72837401 2.03747261 9.00850971
C -3.33731163 0.95826558 11.13202357
C -2.73260053 2.02861698 10.42947584
C -3.34153815 0.94940994 12.55298970
C -2.74105356 2.01090573 13.27140807
C -3.34999119 0.93169869 15.39492194
C -2.74528008 2.00205010 14.69237419
C -3.35421771 0.92284306 16.81588806
C -2.75373312 1.98433883 17.53430644
C -3.36267075 0.90513180 19.65782029
C -2.75795964 1.97548321 18.95527256
C -3.36689726 0.89627617 21.07878642
C -2.76641267 1.95777195 21.79720479
C -3.37535029 0.87856491 23.92071866
C -2.77063919 1.94891632 23.21817091
C -3.37957681 0.86970928 25.34168478
C -2.77909222 1.93120506 26.06010316
C -3.27936794 -1.37307333 -1.67163818
C -3.50010132 -0.16513255 -2.37578365
C -3.28359445 -1.38192895 -0.25067206
C -3.50855436 -0.18284381 0.46614859
C -3.29204749 -1.39964022 2.59126017
C -3.51278088 -0.19169943 1.88711471
C -3.29627401 -1.40849585 4.01222630
C -3.52123391 -0.20941070 4.72904695
C -3.30472705 -1.42620710 6.85415854
C -3.52546043 -0.21826633 6.15001307
C -3.30895357 -1.43506273 8.27512466
C -3.53391347 -0.23597758 8.99194531
C -3.31740661 -1.45277399 11.11705690
C -3.53813999 -0.24483321 10.41291143
C -3.32163312 -1.46162962 12.53802302
C -3.54659303 -0.26254447 13.25484367
C -3.33008615 -1.47934088 15.37995526
C -3.55081955 -0.27140010 14.67580979
C -3.33431267 -1.48819650 16.80092138
C -3.55927257 -0.28911136 17.51774203
C -3.34276571 -1.50590777 19.64285362
C -3.56349909 -0.29796698 18.93870814
C -3.34699223 -1.51476340 21.06381974
C -3.57195213 -0.31567825 21.78064039
C -3.35544527 -1.53247465 23.90575198
C -3.57617865 -0.32453388 23.20160651
C -3.35967178 -1.54133028 25.32671810
C -3.58463169 -0.34224513 26.04353875
C -1.71309129 -3.20749110 -1.67841176
C -2.65595025 -2.42371268 -2.38734855
C -1.71731781 -3.21634673 -0.25744564
C -2.66440328 -2.44142394 0.45458369
C -1.72577085 -3.23405799 2.58448660
C -2.66862979 -2.45027956 1.87554981
C -1.72999736 -3.24291362 4.00545272
C -2.67708283 -2.46799083 4.71748205
C -1.73845039 -3.26062488 6.84738496
C -2.68130935 -2.47684646 6.13844817
C -1.74267691 -3.26948050 8.26835108
C -2.68976239 -2.49455771 8.98038041
C -1.75112995 -3.28719177 11.11028332
C -2.69398891 -2.50341334 10.40134653
C -1.75535647 -3.29604740 12.53124944
C -2.70244194 -2.52112460 13.24327877
C -1.76380951 -3.31375865 15.37318168
C -2.70666846 -2.52998023 14.66424489
C -1.76803602 -3.32261428 16.79414780
C -2.71512150 -2.54769149 17.50617713
C -1.77648906 -3.34032554 19.63608004
C -2.71934802 -2.55654711 18.92714325
C -1.78071558 -3.34918117 21.05704616
C -2.72780105 -2.57425838 21.76907549
C -1.78916862 -3.36689243 23.89897840
C -2.73202757 -2.58311401 23.19004161
C -1.79339513 -3.37574805 25.31994452
C -2.74048060 -2.60082526 26.03197385
C 0.66546662 -3.60577136 -1.67381911
C -0.55726051 -3.61185665 -2.38851086
C 0.66124011 -3.61462699 -0.25285300
C -0.56571355 -3.62956791 0.45342137
C 0.65278707 -3.63233825 2.58907925
C -0.56994007 -3.63842353 1.87438749
C 0.64856056 -3.64119388 4.01004537
C -0.57839311 -3.65613479 4.71631974
C 0.64010752 -3.65890514 6.85197760
C -0.58261963 -3.66499043 6.13728586
C 0.63588100 -3.66776076 8.27294372
C -0.59107266 -3.68270168 8.97921809
C 0.62742796 -3.68547203 11.11487597
C -0.59529918 -3.69155731 10.40018421
C 0.62320144 -3.69432766 12.53584209
C -0.60375222 -3.70926857 13.24211646
C 0.61474840 -3.71203891 15.37777432
C -0.60797874 -3.71812420 14.66308258
C 0.61052189 -3.72089454 16.79874045
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C 0.60206886 -3.73860580 19.64067269
C -0.62065829 -3.74469108 18.92598093
C 0.59784234 -3.74746143 21.06163881
C -0.62911132 -3.76240235 21.76791318
C 0.58938930 -3.76517268 23.90357104
C -0.63333784 -3.77125798 23.18887929
C 0.58516278 -3.77402831 25.32453717
C -0.64179088 -3.78896923 26.03081153
C 2.74330874 -2.38254178 -1.66001547
C 1.81455560 -3.17282422 -2.37872004
C 2.73908222 -2.39139741 -0.23904936
C 1.80610256 -3.19053548 0.46321220
C 2.73062919 -2.40910866 2.60288289
C 1.80187604 -3.19939112 1.88417832
C 2.72640267 -2.41796430 4.02384901
C 1.79342300 -3.21710237 4.72611056
C 2.71794963 -2.43567556 6.86578124
C 1.78919648 -3.22595800 6.14707668
C 2.71372311 -2.44453118 8.28674736
C 1.78074345 -3.24366925 8.98900892
C 2.70527007 -2.46224244 11.12867961
C 1.77651693 -3.25252489 10.40997504
C 2.70104355 -2.47109808 12.54964573
C 1.76806389 -3.27023615 13.25190728
C 2.69259053 -2.48880933 15.39157796
C 1.76383738 -3.27909177 14.67287340
C 2.68836401 -2.49766496 16.81254409
C 1.75538434 -3.29680303 17.51480564
C 2.67991097 -2.51537621 19.65447633
C 1.75115782 -3.30565867 18.93577176
C 2.67568445 -2.52423185 21.07544245
C 1.74270479 -3.32336992 21.77770400
C 2.66723141 -2.54194311 23.91737468
C 1.73847827 -3.33222555 23.19867012
C 2.66300489 -2.55079873 25.33834081
C 1.73002523 -3.34993680 26.04060236
O 0.24405800 -0.43246300 18.26757300
H 0.77092200 0.33384200 18.50360100
H 0.35440300 -0.51877600 17.30805700
O -0.34240290 -0.04819132 7.31223093
H -0.27175885 0.90196464 7.43504817
H -0.52683913 -0.17707850 6.37836139
O -0.33993000 0.05511600 12.74911400
H -0.02096700 0.96043300 12.74595900
H -0.41904900 -0.17279300 11.80784600
O -0.11010500 -0.28129800 15.48958600
H -0.10862400 -0.41842600 14.52796700
H -1.01172700 -0.02024900 15.69152400
O -0.04532300 -0.26090600 10.00878900
H 0.86929000 -0.53950700 9.92666700
H -0.34330300 -0.15252400 9.09251300
O -1.03367527 -0.19737191 4.66340888
H -0.93326094 -0.15341279 3.70968746
H -1.91739883 0.08851425 4.90610575
$end

$opt
FIXED
1 XYZ
2 XYZ
3 XYZ
4 XYZ
5 XYZ
6 XYZ
7 XYZ
8 XYZ
9 XYZ
10 XYZ
11 XYZ
12 XYZ
13 XYZ
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29 XYZ
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31 XYZ
32 XYZ
33 XYZ
34 XYZ
35 XYZ
36 XYZ
37 XYZ
38 XYZ
39 XYZ
40 XYZ
41 XYZ
42 XYZ
43 XYZ
44 XYZ
45 XYZ
46 XYZ
47 XYZ
48 XYZ
49 XYZ
50 XYZ
51 XYZ
52 XYZ
53 XYZ
54 XYZ
55 XYZ
56 XYZ
57 XYZ
58 XYZ
59 XYZ
60 XYZ
61 XYZ
62 XYZ
63 XYZ
64 XYZ
65 XYZ
66 XYZ
67 XYZ
68 XYZ
69 XYZ
70 XYZ
71 XYZ
72 XYZ
73 XYZ
74 XYZ
75 XYZ
76 XYZ
77 XYZ
78 XYZ
79 XYZ
80 XYZ
81 XYZ
82 XYZ
83 XYZ
84 XYZ
85 XYZ
86 XYZ
87 XYZ
88 XYZ
89 XYZ
90 XYZ
91 XYZ
92 XYZ
93 XYZ
94 XYZ
95 XYZ
96 XYZ
97 XYZ
98 XYZ
99 XYZ
100 XYZ
101 XYZ
102 XYZ
103 XYZ
104 XYZ
105 XYZ
106 XYZ
107 XYZ
108 XYZ
109 XYZ
110 XYZ
111 XYZ
112 XYZ
113 XYZ
114 XYZ
115 XYZ
116 XYZ
117 XYZ
118 XYZ
119 XYZ
120 XYZ
121 XYZ
122 XYZ
123 XYZ
124 XYZ
125 XYZ
126 XYZ
127 XYZ
128 XYZ
129 XYZ
130 XYZ
131 XYZ
132 XYZ
133 XYZ
134 XYZ
135 XYZ
136 XYZ
137 XYZ
138 XYZ
139 XYZ
140 XYZ
141 XYZ
142 XYZ
143 XYZ
144 XYZ
145 XYZ
146 XYZ
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148 XYZ
149 XYZ
150 XYZ
151 XYZ
152 XYZ
153 XYZ
154 XYZ
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156 XYZ
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158 XYZ
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160 XYZ
161 XYZ
162 XYZ
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164 XYZ
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167 XYZ
168 XYZ
169 XYZ
170 XYZ
171 XYZ
172 XYZ
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174 XYZ
175 XYZ
176 XYZ
177 XYZ
178 XYZ
179 XYZ
180 XYZ
181 XYZ
182 XYZ
183 XYZ
184 XYZ
185 XYZ
186 XYZ
187 XYZ
188 XYZ
189 XYZ
190 XYZ
191 XYZ
192 XYZ
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194 XYZ
195 XYZ
196 XYZ
197 XYZ
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218 XYZ
219 XYZ
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242 XYZ
243 XYZ
244 XYZ
245 XYZ
246 XYZ
247 XYZ
248 XYZ
249 XYZ
250 XYZ
251 XYZ
252 XYZ
ENDFIXED
$end

Output file is as follows:
A cutoff of 1.0D-14 yielded2953865 shell pairs
There are 27952301 function pairs ( 38043563 Cartesian)
Smallest overlap matrix eigenvalue = 1.26E-15
Linear dependence detected in AO basis
Tighter screening thresholds may be required for diffuse basis sets
Use S2THRESH > 14 and THRESH = 14 in case of SCF convergence issues
Number of orthogonalized atomic orbitals = 11247
Maximum deviation from orthogonality = 6.993E-10

Scale SEOQF with 1.000000e-01/1.000000e-01/1.000000e-03

Standard Electronic Orientation quadrupole field applied
Nucleus-field energy = 0.0000006568 hartrees
Guess from superposition of atomic densities
Warning: Energy on first SCF cycle will be non-variational
SAD guess density has 1571.999995 electrons


General SCF calculation program by
Eric Jon Sundstrom, Paul Horn, Yuezhi Mao, Dmitri Zuev, Alec White,
David Stuck, Shaama M.S., Shane Yost, Joonho Lee, David Small,
Daniel Levine, Susi Lehtola, Hugh Burton, Evgeny Epifanovsky,
Bang C. Huynh

Exchange: 0.5400 Hartree-Fock + 1.0000 M06-2X
Correlation: 1.0000 M06-2X
Using Euler-Maclaurin-Lebedev (99,590) quadrature formula
Dispersion: Grimme D3
using 8 threads for integral computing

OpenMP Integral computing Module
Release: version 1.0, May 2013, Q-Chem Inc. Pittsburgh

A restricted SCF calculation will be
performed using DIIS
SCF converges when DIIS error is below 1.0e-08

Cycle Energy DIIS error

There is not obvious error.Waiting for your reply.

A few comments:
(1) Constrained optimizations often take numerous cycles to complete. Here, you are fixed the positions of a lot of atoms so you may be setting yourself up for a lot of optimization steps.
(2) That is even more so because you have significantly tightened the convergence criteria for the optimization.
(3) Finally, using a triplet-zeta basis set with diffuse functions is almost certainly overkill for a geometry optimization with M06-2X+D3. I might suggest 6-31G(d) instead.
(4) As for what looks like a crash (?), It would be easier if you could paste the end of the Q-Chem output file in preformatted text (see the buttons on the GUI), so that I can see the error without the text being reformatted by the GUI.

We have currently modified the input file according to your suggestion and have tried to optimise it by using “frozen” and “fixed” atoms, but we find that the calculation is still very slow. It is reasonable to assume that freezing most systems and calculating systems with only about 20 atoms is fast, so why is this the case? I would be grateful for your help.

Can you please define what you mean by “slow”? Independent of any constraints, each optimization cycle may take a long time because the system is large (and because you have tightened the convergence thresholds); that’s why I suggested a smaller basis set. On top of that, introduction of constraints generally leads to more optimization cycles required and while I don’t have experience running calculations that are as highly constrained as this one, it would not surprise me to learn that the numerous constraints lead to a large number of optimization steps being required.