Hello Yuvam,
Normally, there is no need to use scripts for geometry optimization. There
are keywords in order to set up the type of optimization you want. For
example, the keyword *MD.VariableCell* if set to *.true.* (together with
the keyword *MD.NumCGsteps* with a value different than cero), indicates
the full system optimization (lattice and atoms), whereas if set to
*.false.* (the default) will optimize only the atom positions.
About your second question, SIESTA is faster and much more efficient than
QE. Just to give you an idea: a colleague of me was running a geometry
optimization for an AuAg alloy in his workstation with 20 cores and 64GB
RAM and didn't get convergence in weeks. I successfully run the same
simulation on my desktop (8 cores & 16GB RAM) in 4 hours :)
An example of input file (with lattice optimization is bellow.
Regards,
Camps
*#############################################################################SystemLabel
all_variableNumberOfAtoms 136NumberOfSpecies 4%block
ChemicalSpeciesLabel 1 1 H 2 6 C 3 7 N 4 8 O%endblock
ChemicalSpeciesLabelLatticeConstant 1.0 Ang%block LatticeParameters
10.581000 7.928000 16.553000 90.000000 107.727000 90.000000%endblock
LatticeParametersAtomicCoordinatesFormat NotScaledCartesianAng%block
AtomicCoordinatesAndAtomicSpecies 1.91076663 1.06761342 15.24602191
4 1 O 0.88997380 0.89272589 8.85534731 3 2 N
0.61149612 0.68841552 11.25381561 2 3 C -0.37800408
0.87639499 4.79519096 2 4 C 0.17716428 0.47923136
9.86087998 2 5 C 2.13452801 1.75492777 12.87753202 2
6 C 1.67113422 1.58737973 11.55716550 2 7 C
-0.81400550 0.98991415 3.36835751 2 8 C -0.89278897
1.27134767 7.17038679 2 9 C 1.29944874 0.36580952
6.51695994 2 10 C 1.52803990 1.00682960 13.92714439 2
11 C 0.43935996 0.13522161 13.64432263 2 12 C
0.90257864 0.37810522 5.17019135 2 13 C 0.41120560
0.81564806 7.54080575 2 14 C -0.02161433 -0.00907599
12.32406669 2 15 C -1.26445923 1.31374798 5.81631769 2
16 C 2.90908407 2.04185648 15.63433950 2 17 C
0.18917149 0.57069532 2.29067770 2 18 C -1.95869884
1.39177163 3.06824363 4 19 O -2.24342476 1.71912263
5.49997151 1 20 H 2.31277866 0.00762706 6.78322120 1
21 H 2.11567889 2.17257368 10.72891688 1 22 H
-0.89145647 -0.66705989 12.12300421 1 23 H 2.94658582
2.47568148 13.07752853 1 24 H 1.61881591 0.01816457
4.40973296 1 25 H -1.59218002 1.63158848 7.94893656 1
26 H 3.07990122 1.88410055 16.72353891 1 27 H
3.86625963 1.88340124 15.08053077 1 28 H -0.04006592
-0.40428223 14.48326591 1 29 H -0.18481235 0.86448272
1.28710652 1 30 H 1.20091261 1.00590456 2.46215283 1
31 H 0.29169576 -0.54136904 2.32642118 1 32 H
2.55398167 3.08091944 15.44449882 1 33 H -0.77656939
-0.08905502 9.70436399 1 34 H 4.51392856 4.05305723
9.70436769 1 35 H 7.84447060 0.88309155 15.44450702 1
36 H 5.58228529 4.50537512 2.32641439 1 37 H
6.49143930 2.95812796 2.46213203 1 38 H 5.10570204
3.09954207 1.28714656 1 39 H 5.25040672 4.36830302
14.48326455 1 40 H 9.15676214 2.08061061 15.08054382 1
41 H 8.37041631 2.07994527 16.72359277 1 42 H
3.69832324 2.33241141 7.94893113 1 43 H 6.90932527
3.94585752 4.40976662 1 44 H 8.23710632 1.48834724
13.07752621 1 45 H 4.39901807 4.63106387 12.12301206 1
46 H 7.40616627 1.79143952 10.72891311 1 47 H
7.60327840 3.95637419 6.78325047 1 48 H 3.04709892
2.24490292 5.49989556 1 49 H 3.33176277 2.57227271
3.06821609 4 50 O 5.47968858 3.39332836 2.29069132 2
51 C 8.19959177 1.92215422 15.63438028 2 52 C
4.02606139 2.65026831 5.81630560 2 53 C 5.26887021
3.97308171 12.32406939 2 54 C 5.70171333 3.14836187
7.54083576 2 55 C 6.19309670 3.58590497 5.17021374 2
56 C 5.72984907 3.82877904 13.64433415 2 57 C
6.81853857 2.95718157 13.92713751 2 58 C 6.58995380
3.59818016 6.51699519 2 59 C 4.39771717 2.69265969
7.17038194 2 60 C 4.47655762 2.97412341 3.36836044 2
61 C 6.96162641 2.37663337 11.55716297 2 62 C
7.42503094 2.20908483 12.87753026 2 63 C 5.46766404
3.48476979 9.86088187 2 64 C 4.91249180 3.08761276
4.79518404 2 65 C 5.90198400 3.27558768 11.25381302 2
66 C 6.18048358 3.07127116 8.85537709 3 67 N
7.20126439 2.89639891 15.24603051 4 68 O 6.31745808
8.01707279 6.06268747 1 69 H 2.98694299 4.84708767
0.32255792 1 70 H 5.24926911 8.46935148 13.44057489 1
71 H 4.34006934 6.92203078 13.30488503 1 72 H
5.72581015 7.06352964 14.47992153 1 73 H 5.58100394
8.33228966 1.28377211 1 74 H 1.67465335 6.04459524
0.68650262 1 75 H 2.46101256 6.04388880 -0.95649531 1
76 H 7.13308095 6.29641155 7.81806789 1 77 H
3.92212031 7.90981106 11.35731791 1 78 H 2.59434561
5.45231590 2.68950384 1 79 H 6.43237602 8.59506488
3.64400808 1 80 H 3.42523714 5.75543166 5.03811195 1
81 H 3.22813611 7.92037353 8.98384381 1 82 H
7.78434662 6.20887472 10.26704171 1 83 H 7.49965667
6.53628337 12.69878439 4 84 O 5.35179252 7.35728593
13.47634999 2 85 C 2.63183240 5.88614298 0.13270314 2
86 C 6.80536550 6.61425410 9.95069602 2 87 C
5.56253228 7.93708804 3.44296477 2 88 C 5.12971213
7.11235859 8.22621482 2 89 C 4.63834434 7.54987223
10.59687032 2 90 C 5.10155729 7.79278613 2.12269636 2
91 C 4.01287741 6.92118065 1.83988087 2 92 C
4.24146591 7.56217291 9.25006082 2 93 C 6.43369789
6.65665654 8.59663522 2 94 C 6.35496412 6.93808665
12.39867190 2 95 C 3.86978612 6.34063653 4.20986726 2
96 C 3.40638951 6.17309097 2.88949800 2 97 C
5.36372830 7.44878555 5.90616886 2 98 C 5.91895138
7.05158791 10.97183601 2 99 C 4.92941549 7.23959959
4.51322334 2 100 C 4.65092226 7.03529291 6.91167328 3
101 N 3.63015106 6.86039781 0.52101182 4 102 O
1.02697316 3.87494005 6.06266860 1 103 H -2.30354869
7.04490968 0.32250657 1 104 H -0.04131541 3.42262201
13.44057898 1 105 H -0.95051297 4.96988347 13.30487987 1
106 H 0.43521204 4.82845768 14.47990359 1 107 H
0.29050577 3.55970341 1.28376237 1 108 H -3.61585165
5.84740255 0.68647813 1 109 H -2.82948955 5.84807674
-0.95654164 1 110 H 1.84259004 5.59558119 7.81807355 1
111 H -1.36840571 3.98217073 11.35728228 1 112 H
-2.69617668 6.43967789 2.68949498 1 113 H 1.14192087
3.29693718 3.64400838 1 114 H -1.86525891 6.13656914
5.03811351 1 115 H -2.06236001 3.97162378 8.98381267 1
116 H 2.49383848 5.68311082 10.26707327 1 117 H
2.20911849 5.35577252 12.69880428 4 118 O 0.06122981
4.53467718 13.47634298 2 119 C -2.65866981 6.00584812
0.13266313 2 120 C 1.51486800 5.27773564 9.95070481 2
121 C 0.27204473 3.95490643 3.44295752 2 122 C
-0.16079281 4.77964898 8.22620936 2 123 C -0.65216889
4.34211452 10.59683739 2 124 C -0.18893750 4.09922289
2.12269577 2 125 C -1.27762743 4.97082526 1.83988167 2
126 C -1.04902977 4.32982786 9.25005756 2 127 C
1.14320206 5.23534347 8.59663389 2 128 C 1.06438751
4.95391639 12.39867636 2 129 C -1.42071482 5.55137919
4.20985881 2 130 C -1.88411245 5.71892771 2.88948937 2
131 C 0.07323513 4.44323483 5.90615518 2 132 C
0.62843199 4.84040154 10.97184165 2 133 C -0.36107741
4.65241176 4.51321078 2 134 C -0.63957921 4.85672810
6.91166860 3 135 N -1.66035251 5.03160237 0.52099878 4
136 O%endblock AtomicCoordinatesAndAtomicSpeciesPAO.BasisSize
DZPMD.TypeOfRun CGMD.NumCGsteps 1000MD.VariableCell
.true.MaxSCFIterations 1000SpinPolarized .true.MeshCutoff 300.0
RyDM.MixingWeight 0.01DM.NumberPulay 3DM.Tolerance
0.001XC.functional VDWXC.authors KBMSolutionMethod
diagonMD.UseSaveXV .true. MD.UseSaveCG .true.DM.UseSaveDM
.true.#WriteEigenvalues .true.#WriteWaveFunctions
.true.#WriteMullikenPop 1#WriteDenchar
.true.#WriteHirshfeldPop .true.#WriteVoronoiPop .true.SaveRho
.true.SaveDeltaRho .true.SaveTotalCharge
.true.SaveElectrostaticPotential .true.SaveBaderCharge
.true.UseSaveData .true. #%block kgrid_Monkhorst_Pack# 8 0 0
0.0# 0 8 0 0.0# 0 0 8 0.0#%endblock kgrid_Monkhorst_Pack#%block
ProjectedDensityOfStates#-9.5 0.5 0.200 1000 eV#%endblock
ProjectedDensityOfStates*
#############################################################################
On Sat, Jun 6, 2020 at 5:00 PM Yuvam Bhateja <[email protected]> wrote:
> Hello everyone,
>
> My name is Yuvam and I am an undergraduate student from Kolkata, India. I
> am new in siesta and have some experience with softwares like Quantum
> ESPRESSO. I want to perform geometrical optimization of my unit cell
> (atomic position as well as cell vectors). I have created my custom made
> unit cell to accommodate the graphene as well as metal oxide for gas
> sensing. I was following a tutorial in which they used scripts for
> optimization but I find it very confusing and very unsuitable as varying
> all 9 values of lattice vector using loops was very cumbersome.
> Can someone help provide any other method in which system does it by its
> own like in QE?
> And also, how fast is siesta as compared to other codes like QE, as my
> system consists of 200-300 atoms and using a cluster with 8 cores and 42 GB
> RAM.
>
> Thank you in advance.
>
> Regards
> Yuvam Bhateja
> B.Tech. 3rd year
> E&Tc
> IIEST Shibpur
>
>
>
> --
> SIESTA is supported by the Spanish Research Agency (AEI) and by the
> European H2020 MaX Centre of Excellence (http://www.max-centre.eu/)
>
--
SIESTA is supported by the Spanish Research Agency (AEI) and by the European
H2020 MaX Centre of Excellence (http://www.max-centre.eu/)
