Pith Number
pith:QCQN42OT
pith:2021:QCQN42OTB3UXD5ABATAY6XT7PJ
not attested
not anchored
not stored
refs pending
Machine learning of microscopic ingredients for graphene oxide/cellulose interaction
arxiv:2107.01040 v1 · 2021-07-02 · cond-mat.mtrl-sci
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{QCQN42OTB3UXD5ABATAY6XT7PJ}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
· sign in to
claim
4
Citations
5
Replications
✓
Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-07-05T06:12:21.963713Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
80a0de69d30ee971f40104c18f5e7f7a6485f32317d27f4f3c3192553cb7a7dc
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QCQN42OTB3UXD5ABATAY6XT7PJ \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 80a0de69d30ee971f40104c18f5e7f7a6485f32317d27f4f3c3192553cb7a7dc
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "51a3c3f319294d9e98bf764d42857372278e270e75e5691b393e30043c2ab179",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cond-mat.mtrl-sci",
"submitted_at": "2021-07-02T12:47:48Z",
"title_canon_sha256": "f1e632a0a02121485017503623c98e5fac295203f5dfc719a37557ad7d13ed88"
},
"schema_version": "1.0",
"source": {
"id": "2107.01040",
"kind": "arxiv",
"version": 1
}
}