Pith Number

pith:MOFA7QDW

pith:2026:MOFA7QDWBHCNGMULRUR3Y6CUQ4

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Dynamical Simulation of On-axis Transmission Kikuchi and Spot Diffraction Patterns, Based on Accurate Diffraction Geometry Calibration

Aimo Winkelmann, Raynald Gauvin, T. Ben Britton, Tianbi Zhang

Accurate diffraction geometry calibration enables dynamical simulations that reproduce spots and other features in on-axis transmission Kikuchi patterns.

arxiv:2603.22628 v2 · 2026-03-23 · cond-mat.mtrl-sci

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Claims

C1strongest claim

By introducing appropriate weight factors, simulation of incoherent diffuse intensity, and calculation of the energy spectra of diffracted electrons, simulated patterns can be obtained which accurately capture the many diffraction features on experimental patterns.

C2weakest assumption

The proposed diffraction geometry calibration routine based on the electron channeling pattern of the direct electron detector accurately accounts for the position of diffraction spots in both geometric and dynamical simulations.

C3one line summary

A diffraction geometry calibration based on electron channeling patterns enables dynamical simulations that match experimental on-axis transmission Kikuchi patterns including spots and excess-deficiency effects.

Cited by

2 papers in Pith

Orientation Mapping via Dictionary Indexing of AC-STEM Kikuchi patterns using Open-source Software

Channeling-in channeling-out revisited: selected area electron channeling and electron backscatter diffraction

Receipt and verification

First computed	2026-05-22T02:04:40.425491Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

638a0fc07609c4d3328b8d23bc785487008aed9ef45d677f7202ea9f86b85ffa

Aliases

arxiv: 2603.22628 · arxiv_version: 2603.22628v2 · doi: 10.48550/arxiv.2603.22628 · pith_short_12: MOFA7QDWBHCN · pith_short_16: MOFA7QDWBHCNGMUL · pith_short_8: MOFA7QDW

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/MOFA7QDWBHCNGMULRUR3Y6CUQ4 \
  | 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: 638a0fc07609c4d3328b8d23bc785487008aed9ef45d677f7202ea9f86b85ffa

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6813c0deac81ccd2b31ffb8da2d21e9b50fe002a1c5b9c7812a8a14389efc98d",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cond-mat.mtrl-sci",
    "submitted_at": "2026-03-23T23:04:28Z",
    "title_canon_sha256": "43bf35b16c600c752ac10a1aa7567c337e4746d8c83cf9ba717b997b55694908"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2603.22628",
    "kind": "arxiv",
    "version": 2
  }
}