Extending the cut-off radius for amorphous silicon using re-run

Hello Lammps users,

I am new to using Lammps and my goal is to plot the radial distribution function vs r for amorphous silicon.
Using my original code, I could plot the radial distribution function vs r up until the cut-off radius (approx. 3.8 Angstroms) given by the Stilinger-
Weber potential but I would like to plot up until 10 Angstroms. I read some articles/Q&A responses that I can use the rerun command to extend the cut-off radius but I am not sure how to implement it for Stilinger Weber potential. If someone could give me some tips or suggestions, I’d really appreciate it. In addition, I also get the coordination numbers at each bin center but the coordination number varies with bin locations in contrast to what I was expecting: around 4 for silicon. If someone could help me with this, that’d be awesome.

Thanks for your time and effort,

Jaeyun

I copy my relevant files here:

i) My original input file that give me up to 3.8 Angstrom

amorphous Si via Stilinger Weber

units metal
atom_style atomic

dimension 3
boundary p p p
read_data annealed_aSi.data

pair_style sw
pair_coeff * * Si.sw Si
neighbor 2.0 multi
neigh_modify every 2 delay 4 check yes

##Simulation Variables
#variable temp equal 300 # temperature to be set
#variable dt equal 0.0005 # timestep to be used 0.5 fs
#variable volume equal 1908839.001 # molecule volume

compute myRDF all rdf 500
fix 1 all ave/time 1000 10 10000 c_myRDF ave window 2 file rdf.out mode vector
run 50000

ii) My own implemented input file for up to 10 Angstrom

amorphous Si via Stilinger Weber

units metal
atom_style atomic

dimension 3
boundary p p p
read_data annealed_aSi.data

pair_style sw
pair_coeff * * Si.sw Si
neighbor 2.0 multi
neigh_modify every 2 delay 4 check yes

##Simulation Variables
#variable temp equal 300 # temperature to be set
#variable dt equal 0.0005 # timestep to be used 0.5 fs
#variable volume equal 1908839.001 # molecule volume

dump rdf all atom 1000 dump.file
compute myRDF all rdf 500
fix 1 all ave/time 1000 10 10000 c_myRDF ave window 2 file rdf.out mode vector
run 50000
rerun dump.file dump x y z

iii)my output file (rdf.out) produced by the i) original input file (Here, I have only included data only up until 10000)

Time-averaged data for fix 1

TimeStep Number-of-rows

Row c_myRDF[1] c_myRDF[2] c_myRDF[3]

10000 500
1 0.00377118 0 0
2 0.0113135 0 0
3 0.0188559 0 0
4 0.0263983 0 0
5 0.0339406 0 0
6 0.041483 0 0
7 0.0490253 0 0
8 0.0565677 0 0
9 0.0641101 0 0
10 0.0716524 0 0
11 0.0791948 0 0
12 0.0867371 0 0
13 0.0942795 0 0
14 0.101822 0 0
15 0.109364 0 0
16 0.116907 0 0
17 0.124449 0 0
18 0.131991 0 0
19 0.139534 0 0
20 0.147076 0 0
21 0.154618 0 0
22 0.162161 0 0
23 0.169703 0 0
24 0.177245 0 0
25 0.184788 0 0
26 0.19233 0 0
27 0.199873 0 0
28 0.207415 0 0
29 0.214957 0 0
30 0.2225 0 0
31 0.230042 0 0
32 0.237584 0 0
33 0.245127 0 0
34 0.252669 0 0
35 0.260211 0 0
36 0.267754 0 0
37 0.275296 0 0
38 0.282839 0 0
39 0.290381 0 0
40 0.297923 0 0
41 0.305466 0 0
42 0.313008 0 0
43 0.32055 0 0
44 0.328093 0 0
45 0.335635 0 0
46 0.343177 0 0
47 0.35072 0 0
48 0.358262 0 0
49 0.365804 0 0
50 0.373347 0 0
51 0.380889 0 0
52 0.388432 0 0
53 0.395974 0 0
54 0.403516 0 0
55 0.411059 0 0
56 0.418601 0 0
57 0.426143 0 0
58 0.433686 0 0
59 0.441228 0 0
60 0.44877 0 0
61 0.456313 0 0
62 0.463855 0 0
63 0.471398 0 0
64 0.47894 0 0
65 0.486482 0 0
66 0.494025 0 0
67 0.501567 0 0
68 0.509109 0 0
69 0.516652 0 0
70 0.524194 0 0
71 0.531736 0 0
72 0.539279 0 0
73 0.546821 0 0
74 0.554363 0 0
75 0.561906 0 0
76 0.569448 0 0
77 0.576991 0 0
78 0.584533 0 0
79 0.592075 0 0
80 0.599618 0 0
81 0.60716 0 0
82 0.614702 0 0
83 0.622245 0 0
84 0.629787 0 0
85 0.637329 0 0
86 0.644872 0 0
87 0.652414 0 0
88 0.659956 0 0
89 0.667499 0 0
90 0.675041 0 0
91 0.682584 0 0
92 0.690126 0 0
93 0.697668 0 0
94 0.705211 0 0
95 0.712753 0 0
96 0.720295 0 0
97 0.727838 0 0
98 0.73538 0 0
99 0.742922 0 0
100 0.750465 0 0
101 0.758007 0 0
102 0.76555 0 0
103 0.773092 0 0
104 0.780634 0 0
105 0.788177 0 0
106 0.795719 0 0
107 0.803261 0 0
108 0.810804 0 0
109 0.818346 0 0
110 0.825888 0 0
111 0.833431 0 0
112 0.840973 0 0
113 0.848516 0 0
114 0.856058 0 0
115 0.8636 0 0
116 0.871143 0 0
117 0.878685 0 0
118 0.886227 0 0
119 0.89377 0 0
120 0.901312 0 0
121 0.908854 0 0
122 0.916397 0 0
123 0.923939 0 0
124 0.931481 0 0
125 0.939024 0 0
126 0.946566 0 0
127 0.954109 0 0
128 0.961651 0 0
129 0.969193 0 0
130 0.976736 0 0
131 0.984278 0 0
132 0.99182 0 0
133 0.999363 0 0
134 1.00691 0 0
135 1.01445 0 0
136 1.02199 0 0
137 1.02953 0 0
138 1.03707 0 0
139 1.04462 0 0
140 1.05216 0 0
141 1.0597 0 0
142 1.06724 0 0
143 1.07479 0 0
144 1.08233 0 0
145 1.08987 0 0
146 1.09741 0 0
147 1.10496 0 0
148 1.1125 0 0
149 1.12004 0 0
150 1.12758 0 0
151 1.13513 0 0
152 1.14267 0 0
153 1.15021 0 0
154 1.15775 0 0
155 1.16529 0 0
156 1.17284 0 0
157 1.18038 0 0
158 1.18792 0 0
159 1.19546 0 0
160 1.20301 0 0
161 1.21055 0 0
162 1.21809 0 0
163 1.22563 0 0
164 1.23318 0 0
165 1.24072 0 0
166 1.24826 0 0
167 1.2558 0 0
168 1.26335 0 0
169 1.27089 0 0
170 1.27843 0 0
171 1.28597 0 0
172 1.29351 0 0
173 1.30106 0 0
174 1.3086 0 0
175 1.31614 0 0
176 1.32368 0 0
177 1.33123 0 0
178 1.33877 0 0
179 1.34631 0 0
180 1.35385 0 0
181 1.3614 0 0
182 1.36894 0 0
183 1.37648 0 0
184 1.38402 0 0
185 1.39157 0 0
186 1.39911 0 0
187 1.40665 0 0
188 1.41419 0 0
189 1.42173 0 0
190 1.42928 0 0
191 1.43682 0 0
192 1.44436 0 0
193 1.4519 0 0
194 1.45945 0 0
195 1.46699 0 0
196 1.47453 0 0
197 1.48207 0 0
198 1.48962 0 0
199 1.49716 0 0
200 1.5047 0 0
201 1.51224 0 0
202 1.51979 0 0
203 1.52733 0 0
204 1.53487 0 0
205 1.54241 0 0
206 1.54995 0 0
207 1.5575 0 0
208 1.56504 0 0
209 1.57258 0 0
210 1.58012 0 0
211 1.58767 0 0
212 1.59521 0 0
213 1.60275 0 0
214 1.61029 0 0
215 1.61784 0 0
216 1.62538 0 0
217 1.63292 0 0
218 1.64046 0 0
219 1.64801 0 0
220 1.65555 0 0
221 1.66309 0 0
222 1.67063 0 0
223 1.67818 0 0
224 1.68572 0 0
225 1.69326 0 0
226 1.7008 0 0
227 1.70834 0 0
228 1.71589 0 0
229 1.72343 0 0
230 1.73097 0 0
231 1.73851 0 0
232 1.74606 0 0
233 1.7536 0 0
234 1.76114 0 0
235 1.76868 0 0
236 1.77623 0 0
237 1.78377 0 0
238 1.79131 0 0
239 1.79885 0 0
240 1.8064 0 0
241 1.81394 0 0
242 1.82148 0 0
243 1.82902 0 0
244 1.83656 0 0
245 1.84411 0 0
246 1.85165 0 0
247 1.85919 0 0
248 1.86673 0 0
249 1.87428 0 0
250 1.88182 0 0
251 1.88936 0 0
252 1.8969 0 0
253 1.90445 0 0
254 1.91199 0 0
255 1.91953 0 0
256 1.92707 0 0
257 1.93462 0 0
258 1.94216 0 0
259 1.9497 0 0
260 1.95724 0 0
261 1.96478 0 0
262 1.97233 0.00103544 2e-05
263 1.97987 0 2e-05
264 1.98741 0 2e-05
265 1.99495 0.00202416 6e-05
266 2.0025 0.00100447 8e-05
267 2.01004 0.000996948 0.0001
268 2.01758 0.00197902 0.00014
269 2.02512 0.00294646 0.0002
270 2.03267 0.00682414 0.00034
271 2.04021 0.00774146 0.0005
272 2.04775 0.0144085 0.0008
273 2.05529 0.0143029 0.0011
274 2.06284 0.0255574 0.00164
275 2.07038 0.0404065 0.0025
276 2.07792 0.0485096 0.00354
277 2.08546 0.0481593 0.00458
278 2.093 0.082753 0.00638
279 2.10055 0.111372 0.00882
280 2.10809 0.150457 0.01214
281 2.11563 0.21508 0.01692
282 2.12317 0.251083 0.02254
283 2.13072 0.325609 0.02988
284 2.13826 0.407889 0.03914
285 2.1458 0.510001 0.0508
286 2.15334 0.580272 0.06416
287 2.16089 0.751339 0.08158
288 2.16843 0.840351 0.1012
289 2.17597 0.978303 0.1242
290 2.18351 1.2512 0.15382
291 2.19106 1.40285 0.18726
292 2.1986 1.57573 0.22508
293 2.20614 1.72304 0.26672
294 2.21368 2.07627 0.31724
295 2.22123 2.29732 0.37352
296 2.22877 2.5356 0.43606
297 2.23631 2.80686 0.50576
298 2.24385 3.00802 0.58096
299 2.25139 3.27716 0.66344
300 2.25894 3.50001 0.75212
301 2.26648 3.75433 0.84788
302 2.27402 4.00209 0.95064
303 2.28156 4.11186 1.05692
304 2.28911 4.20933 1.16644
305 2.29665 4.44977 1.28298
306 2.30419 4.49655 1.40152
307 2.31173 4.54715 1.52218
308 2.31928 4.53036 1.64318
309 2.32682 4.58436 1.76642
310 2.33436 4.50674 1.88836
311 2.3419 4.38595 2.0078
312 2.34945 4.32646 2.12638
313 2.35699 4.17991 2.24168
314 2.36453 4.1468 2.3568
315 2.37207 4.01023 2.46884
316 2.37961 3.81413 2.57608
317 2.38716 3.62537 2.67866
318 2.3947 3.42276 2.77612
319 2.40224 3.1584 2.86662
320 2.40978 3.11022 2.9563
321 2.41733 2.91369 3.04084
322 2.42487 2.65378 3.11832
323 2.43241 2.35619 3.18754
324 2.43995 2.23271 3.25354
325 2.4475 2.08987 3.3157
326 2.45504 1.88592 3.37214
327 2.46258 1.72294 3.42402
328 2.47012 1.58107 3.47192
329 2.47767 1.41857 3.51516
330 2.48521 1.32846 3.5559
331 2.49275 1.15319 3.59148
332 2.50029 1.09727 3.62554
333 2.50783 0.985009 3.6563
334 2.51538 0.875343 3.6838
335 2.52292 0.822656 3.7098
336 2.53046 0.757371 3.73388
337 2.538 0.702226 3.75634
338 2.54555 0.635288 3.77678
339 2.55309 0.602497 3.79628
340 2.56063 0.521549 3.81326
341 2.56817 0.452534 3.82808
342 2.57572 0.432281 3.84232
343 2.58326 0.400788 3.8556
344 2.5908 0.379255 3.86824
345 2.59834 0.352595 3.88006
346 2.60589 0.309036 3.89048
347 2.61343 0.281306 3.90002
348 2.62097 0.265617 3.90908
349 2.62851 0.265844 3.9182
350 2.63605 0.250993 3.92686
351 2.6436 0.237459 3.9351
352 2.65114 0.210321 3.94244
353 2.65868 0.222805 3.95026
354 2.66622 0.218714 3.95798
355 2.67377 0.178042 3.9643
356 2.68131 0.189367 3.97106
357 2.68885 0.168807 3.97712
358 2.69639 0.166756 3.98314
359 2.70394 0.158665 3.9889
360 2.71148 0.163262 3.99486
361 2.71902 0.147648 4.00028
362 2.72656 0.154417 4.00598
363 2.73411 0.140634 4.0112
364 2.74165 0.14522 4.01662
365 2.74919 0.129503 4.02148
366 2.75673 0.125085 4.0262
367 2.76427 0.13231 4.03122
368 2.77182 0.116387 4.03566
369 2.77936 0.122014 4.04034
370 2.7869 0.115131 4.04478
371 2.79444 0.13669 4.05008
372 2.80199 0.125181 4.05496
373 2.80953 0.104609 4.05906
374 2.81707 0.101004 4.06304
375 2.82461 0.125203 4.068
376 2.83216 0.0949094 4.07178
377 2.8397 0.128372 4.07692
378 2.84724 0.0958939 4.08078
379 2.85478 0.0939051 4.08458
380 2.86233 0.0929192 4.08836
381 2.86987 0.0992783 4.09242
382 2.87741 0.103623 4.09668
383 2.88495 0.102598 4.10092
384 2.8925 0.104953 4.10528
385 2.90004 0.085729 4.10886
386 2.90758 0.111966 4.11356
387 2.91512 0.106648 4.11806
388 2.92266 0.0966669 4.12216
389 2.93021 0.104145 4.1266
390 2.93775 0.09521 4.13068
391 2.94529 0.114225 4.1356
392 2.95283 0.115952 4.14062
393 2.96038 0.0928409 4.14466
394 2.96792 0.11249 4.14958
395 2.97546 0.0982714 4.1539
396 2.983 0.0950591 4.1581
397 2.99055 0.118 4.16334
398 2.99809 0.107997 4.16816
399 3.00563 0.105226 4.17288
400 3.01317 0.110024 4.17784
401 3.02072 0.112123 4.18292
402 3.02826 0.101463 4.18754
403 3.0358 0.118005 4.19294
404 3.04334 0.113507 4.19816
405 3.05088 0.130688 4.2042
406 3.05843 0.118849 4.20972
407 3.06597 0.130691 4.21582
408 3.07351 0.12536 4.2217
409 3.08105 0.138749 4.22824
410 3.0886 0.134272 4.2346
411 3.09614 0.132779 4.24092
412 3.10368 0.139243 4.24758
413 3.11122 0.151468 4.25486
414 3.11877 0.134172 4.26134
415 3.12631 0.140119 4.26814
416 3.13385 0.148058 4.27536
417 3.14139 0.158777 4.28314
418 3.14894 0.153955 4.29072
419 3.15648 0.1702 4.29914
420 3.16402 0.170999 4.30764
421 3.17156 0.160976 4.31568
422 3.1791 0.175358 4.32448
423 3.18665 0.165009 4.3328
424 3.19419 0.185549 4.3422
425 3.20173 0.192534 4.352
426 3.20927 0.197106 4.36208
427 3.21682 0.203189 4.37252
428 3.22436 0.204177 4.38306
429 3.2319 0.190499 4.39294
430 3.23944 0.217633 4.40428
431 3.24699 0.223882 4.416
432 3.25453 0.232733 4.42824
433 3.26207 0.225601 4.44016
434 3.26961 0.24114 4.45296
435 3.27716 0.243782 4.46596
436 3.2847 0.25237 4.47948
437 3.29224 0.278343 4.49446
438 3.29978 0.273373 4.50924
439 3.30732 0.282807 4.5246
440 3.31487 0.295451 4.54072
441 3.32241 0.291191 4.55668
442 3.32995 0.299318 4.57316
443 3.33749 0.325449 4.59116
444 3.34504 0.318224 4.60884
445 3.35258 0.355138 4.62866
446 3.36012 0.352119 4.6484
447 3.36766 0.378246 4.6697
448 3.37521 0.368779 4.69056
449 3.38275 0.397408 4.71314
450 3.39029 0.427882 4.73756
451 3.39783 0.428078 4.7621
452 3.40538 0.427225 4.7867
453 3.41292 0.465798 4.81364
454 3.42046 0.47855 4.84144
455 3.428 0.511409 4.87128
456 3.43554 0.493809 4.90022
457 3.44309 0.550429 4.93262
458 3.45063 0.567646 4.96618
459 3.45817 0.600201 5.00182
460 3.46571 0.652588 5.04074
461 3.47326 0.673464 5.08108
462 3.4808 0.716094 5.12416
463 3.48834 0.73253 5.16842
464 3.49588 0.809132 5.21752
465 3.50343 0.814513 5.26716
466 3.51097 0.856436 5.31958
467 3.51851 0.910032 5.37552
468 3.52605 0.960894 5.43484
469 3.5336 1.03389 5.49894
470 3.54114 1.07479 5.56586
471 3.54868 1.12204 5.63602
472 3.55622 1.18799 5.71062
473 3.56377 1.2705 5.79074
474 3.57131 1.31756 5.87418
475 3.57885 1.36957 5.96128
476 3.58639 1.423 6.05216
477 3.59393 1.46662 6.14622
478 3.60148 1.57228 6.24748
479 3.60902 1.65416 6.35446
480 3.61656 1.67282 6.4631
481 3.6241 1.73702 6.57638
482 3.63165 1.92405 6.70238
483 3.63919 1.91638 6.8284
484 3.64673 1.94966 6.95714
485 3.65427 2.04478 7.09272
486 3.66182 2.12618 7.23428
487 3.66936 2.18326 7.38024
488 3.6769 2.25922 7.5319
489 3.68444 2.33395 7.68922
490 3.69199 2.36343 7.84918
491 3.69953 2.42885 8.01424
492 3.70707 2.5201 8.1862
493 3.71461 2.53586 8.35994
494 3.72215 2.61514 8.53984
495 3.7297 2.637 8.72198
496 3.73724 2.68203 8.90798
497 3.74478 2.66951 9.09386
498 3.75232 2.7223 9.28418
499 3.75987 2.78376 9.47958
500 3.76741 2.76071 9.67414

Hello Lammps users,

I am new to using Lammps and my goal is to plot the radial distribution
function vs r for amorphous silicon.
Using my original code, I could plot the radial distribution function vs r
up until the cut-off radius (approx. 3.8 Angstroms) given by the Stilinger-
Weber potential but I would like to plot up until 10 Angstroms. I read some
articles/Q&A responses that I can use the rerun command to extend the
cut-off radius but I am not sure how to implement it for Stilinger Weber
potential. If someone could give me some tips or suggestions, I'd really
appreciate it. In addition, I also get the coordination numbers at each bin
center but the coordination number varies with bin locations in contrast to
what I was expecting: around 4 for silicon. If someone could help me with
this, that'd be awesome.

when using re-run to compute a g(r), it doesn't matter which potential
you are using, since the trajectory is already computed, so using
lj/cut with a suitable cutoff will do the trick. only if you are also
interested in the re-computed energies and forces, then you'd have
to play tricks.

axel.

There is no need to use the SW potential in your rerun

script since you aren’t running dynamics. You can just

use a LJ potential and set the cutoff to whatever value

you wish, so that compute rdf will have the neighbors

it needs. The choice of potential does not alter the RDF.

Steve