Pith. sign in

REVIEW 2 major objections 5 minor 32 references

GRADAR: orientation-map-driven detection and ranking of grains for targeted two-beam electron channeling contrast imaging

T0 review · 2 major / 5 minor · reviewed 2026-08-04 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A geometric cone criterion decides which grains of a polycrystal can reach a nominated two-beam condition, and ranking by darkness alone selects the wrong candidates.

desk verdict The forward reachability geometry is solid, simple, and worth referee time; the headline ranking output is honest but unvalidated on polycrystals, so treat the session-plan claim as provisional. read the letter →

arxiv 2608.02400 v1 pith:YMMXXRTL submitted 2026-08-03 cond-mat.mtrl-sci

Johan Ewald Westraadt This is my paper · ORCID
classification cond-mat.mtrl-sci
keywords electronchannelingcontrastimagingtwo-beamconditionEBSDorientationmapreachabilitycriterionstagerotationclearancerankinggraintargetingsimulation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper claims that the tedious per-grain hunt for a two-beam diffraction condition in electron channeling contrast imaging (ECCI) can be inverted: the operator names one reflection family and a stage envelope, and a computed sweep over an EBSD orientation map returns every grain that can reach that family's condition, with the stage rotation and tilt to dial. The reachability test reduces to a two-line inequality: at fixed stage tilt t, the plane normal of a reachable reflection must lie within (t + θ_B) of the specimen surface. On a measured 163-grain austenitic steel map at 20 kV, this makes {111} reachability rise from 38.7% at 7° tilt to 77.3% at 15°, while {220} and {311} already reach 79.8% and 91.4% at 7°. The paper further claims that among reachable grains, picking the darkest candidate is wrong—same-family candidates excite their own band identically at Bragg incidence, so darkness tracks rival-band contamination; the method instead gates candidates on a minimum angular clearance from all rival reflections and ranks the darkest survivor. If true, high-throughput defect studies would switch from per-grain manual alignment to a computed session plan under one declared diffraction vector.

What carries the argument

The central object is the rotation cone: at fixed stage tilt t, stage rotation φ sweeps the incident beam direction around a cone of half-angle t about the specimen normal, in each grain's crystal frame. The reachability criterion is an annulus requiring a plane normal within (t + θ_B) of the specimen surface; it reduces the targeting problem to a two-line geometric check. The ranking mechanism is the clearance gate: for each candidate at a two-beam edge of the nominated family, compute the minimum angular distance from any rival reflection to its own Bragg condition, discard candidates below max(0.5°, θ_B), and rank the rest by predicted channeling darkness. The gearing relation dβ = sin t

What would settle it

A decisive check: on a polycrystalline sample, measure actual dislocation-channeling contrast at the method-selected condition for each grain and compare darkest-clean versus globally darkest candidates; if per-grain contrast does not favor the darkest-clean selection, or if a grain predicted unreachable at a given tilt shows a usable two-beam band edge after all, the ranking or the reachability criterion fails.

Watch

Extended reading notes

Core claim

At fixed stage tilt t, rotating the stage sweeps the incident beam around a cone of half-angle t in each grain's crystal frame. A reflection family with Bragg angle θ_B reaches its two-beam condition exactly when one of its plane normals lies within (t + θ_B) of the specimen surface; this is an annulus on the orientation sphere. The paper shows on a measured 163-grain map that this geometric criterion, not texture intuition, governs usability: {111} reachability jumps from 38.7% at 7° tilt to 77.3% at 15°, and the higher-multiplicity {220}/{311} families outperform {111} at low tilt. For ranking, all same-family candidates are equivalent with respect to their own band at exact Bragg incidenc

Load-bearing premise

The ranking rests on the assumption that every member of the chosen reflection family produces identical channeling darkness at its own Bragg condition, so differences between candidates come only from nearby competing reflections; this premise has not yet been verified grain-by-grain on a polycrystal.

Editorial extensions

If this is right

  • Map-wide ECCI session planning becomes a computed procedure: nominate a diffraction vector and a stage envelope, and get a ranked candidate table with dial-ready stage moves instead of per-grain manual searches.
  • Reachability fractions are strongly stage-tilt dependent: on the measured map at 7° tilt, {111} serves only 38.7% of grains while {220} and {311} serve 79.8% and 91.4%, guiding family choice before the session.
  • The clearance gate implies that scientifically usable candidates are not the darkest; the optimal floor trades contamination margin against yield and darkness, an experimental parameter left to validation.
  • The gearing result means sub-0.1° beam alignment is attainable on an ordinary rotation stage at low tilt, meeting the sub-half-degree precision demand without specialized channeling hardware.
  • The inverse formulation allows statistically representative defect populations to be collected under one declared condition across many grains, enabling comparisons across processing or testing histories.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: the reachability inequality is purely geometric and energy-dependent only through θ_B, so the same annulus criterion should transfer to other channeling-based modalities, such as TEM two-beam settings or other crystal systems, with the stage model modified.
  • Editorial inference: because the sweep depends on one reference orientation plus stage kinematics, the method could be extended to a live feedback loop that recomputes candidates from a locally updated orientation after each stage move, correcting map calibration drift during the session.
  • Editorial inference: the reported positive correlation between predicted intensity and rival clearance suggests a testable meta-prediction: measured per-grain contrast should be higher for darkest-clean candidates than for the globally darkest ones, which the companion polycrystal validation can settle directly.
  • Editorial inference: the random-texture baseline implies that for weakly textured specimens, reachability fractions are near-universal functions of family, energy, and tilt, so session planning could be precomputed from material class alone before any map is taken.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The paper presents GRADAR, a computational procedure that takes an EBSD orientation map of a polycrystal, a nominated reflection family, and a stage tilt/rotation envelope, and determines which grains can be brought to a two-beam electron channeling condition for that family, then ranks the survivors. The central geometric result is eq. (2): at fixed stage tilt t, stage rotation sweeps the incident beam along a cone of half-angle t in each grain's crystal frame, so a plane normal with polar angle α from the specimen normal reaches a Bragg angle θ_B iff α lies within [90°−(t+θ_B), 90°+(t+θ_B)]. This criterion is applied to a measured 163-grain austenitic steel map at 20 kV, producing reachability fractions that vary strongly with tilt and family ({111} rises from 38.7% at 7° to 77.3% at 15°; {220} and {311} reach 79.8% and 91.4% at 7°). A 'darkest-clean' ranking with a rival-clearance gate (eq. 4) is proposed to select among reachable candidates. The predicted precession sweep is checked against the published AstroECP silicon series: the simulated trace correlates at r=0.84 with the SA-ECP centre trace, and the measured intensity is dark at all 16 predicted two-beam edges. Per-grain polycrystal validation of the ranking is explicitly deferred to a companion study.

Significance. If the reachability result is correct, it closes the forward question posed by L'hôte et al. in 2019 and turns map-wide ECCI session planning into a computed procedure: the operator can nominate a g vector and immediately see which grains of a mapped polycrystal can serve it, and at what stage tilt and rotation. The eq. (2) criterion is parameter-free and hand-checkable; the reachability tables are deterministic computations on a public dataset with a disclosed random-texture baseline; the implementation is reproducible via shipped notebooks, with two independent implementations agreeing to <0.006° in crossing angles. The experimental check on published silicon data is genuine and anchors the sweep geometry at two levels (orientation fitting and intensity correlation). The main weakness is that the ranking step—the 'R' in GRADAR—is validated only indirectly: an internal correlation of r=+0.40 on the same map's candidates and darkness at 16 predicted edges in a single crystal. Neither test demonstrates that the darkest-clean candidate is the best two-beam condition in a polycrystal. This is disclosed in §6.2, but it is the load-bearing link between the proven geometry and the applie

major comments (2)
  1. [§3 Rank; eq. (4)] The ranking premise—that at exact Bragg incidence all same-family candidates are equivalent with respect to their own band, so intensity differences are dominated by rival contamination—is not theoretically established. In the two-beam dynamical theory, the tie point and branch excitation at sg=0 depend on the boundary conditions at the specimen surface, which vary along the Kossel cone as the orientation of the diffracting planes relative to the surface changes; the 'own-band' contribution may therefore not be identical for all candidates. The paper's empirical support is the internal correlation r=+0.40 (§4) and the single-crystal dark-at-16-edges check (§5). Neither tests the ranking across a polycrystal. Because the ranked candidate table is the main output of the tool, this is load-bearing. The manuscript should either derive the equivalence from a suitable dynamical model, present
  2. [§5; Table 2; §6.2] The experimental validation is confined to a single [001] silicon crystal at ~7° tilt and does not exercise the ranking across grains. The r=+0.40 correlation in §4 is computed on 244 candidates from 163 grains, with multiple candidates per grain, so the effective number of independent observations is smaller and within-grain clustering is not accounted for; moreover, a correlation with rival clearance only supports the contamination gradient, not the correctness of the darkest-clean choice. A dedicated experiment comparing predicted dark-clean candidates with measured dislocation contrast in several grains of a polycrystal is necessary to support the session-plan output. As written, the paper's strongest validated contribution is the reachability geometry; the ranking contribution remains unsupported.
minor comments (5)
  1. [§4, Table 1] The random-texture baseline paragraph says 'The exact isotropic value sits between the two' (single-plane probability and union bound). Please give the actual Monte-Carlo value in the text for {111} at 7°, and add the union-bound row to Table 1 or state it explicitly; the current wording is slightly unclear.
  2. [§5, Figure 8] The BSE trace comparison uses a linear detrend and a −3° lag, but neither is visible in Figure 8. Please mark the detrend and the lag in the figure or its caption so that the reader can see what was adjusted.
  3. [§3, eq. (4)] The notation γ_r = |90° − angle(k, g_r)| is understandable but the subscript braces and the absolute value could be annotated. Also, 'kinematically forbidden rivals are dropped by structure factor' should specify whether the structure-factor cut-off is user-configurable.
  4. [Table 2] The column header 'gRotation (deg)' is ambiguous; consider splitting it into 'g' and 'Stage rotation (°)' for clarity.
  5. [§6.3] The statement that the code is 'available from the author while the public release archive is being prepared' is at odds with the reproducibility promise. A permanent DOI or repository link would make the reproducibility claim fully checkable.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the reachability criterion is derived geometry, and validation uses external published data.

full rationale

The central reachability criterion (eq. 2) is derived directly from the stated cone geometry and the Bragg condition, with no parameter fitted to the reachability percentages; the measured-map fractions and random-texture baselines are direct evaluations of that closed-form condition. The ranking step rests on an explicit physical premise (same-family equivalence at exact Bragg, with the rival-clearance gate of eq. 4) whose per-grain polycrystal validation the paper openly defers in §6.2: 'per-grain ranking across a polycrystal has not been validated against measured contrast; that closure is deferred to a companion study.' That is a disclosed limitation, not a circular reduction. The experimental check in §5 is anchored to the external published AstroECP silicon dataset: the simulated sweep is generated from a reference orientation plus a stage model, with the precession tilt and sense calibrated from the same dataset's indexed directions, but the measured intensity trace is not used to fit the simulated curve. The paper separately reports the r=0.84 SA-ECP correlation, the BSE correlation with disclosed detrend and -3° lag, and the dark-at-16-predicted-edges check. No load-bearing self-citation chain exists: the single author does not cite his own prior work to justify the method, and the central geometry is parameter-free and checkable by hand.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The central reachability criterion (eq. 2) is parameter-free spherical geometry; the fitted quantities live in the validation chain (precession tilt and stage sense from the 73 indexed Si directions; detrend and lag for the BSE trace) and in user choices (clearance floor, stage envelope). No dedicated free parameters are introduced to make the central derivation work. The reliability of the ranking additionally depends on the transfer of the dynamical simulation model from one measured orientation to arbitrary grain orientations, which is the dominant unvalidated assumption.

free parameters (4)
  • Clearance floor max(0.5°, θ_B) = 1.18° for {111} at 20 kV (default), varied 0.5°–6° in table 3
    User-set gate in the Rank step (§3, table 3) that determines which candidates survive. It is a design choice, not fitted to data, but it directly controls the output ranking and yield.
  • Precession-axis tilt and stage sense = tilt = 6.86 ± 0.06°, stage sense pinned empirically
    Fitted to the 73 indexed beam directions of the AstroECP silicon series (§5). This anchors the validation, not the central derivation; the opposite stage sense fails at 13.7°.
  • BSE trace linear detrend and −3° lag = unspecified coefficients; lag −3°
    Acquisition-drift removal and an angular offset applied to the BSE trace before computing r=0.75 (§5). Disclosed as instrumental, but they are fit parameters in the validation chain.
  • RANSAC grain-size filter seed = seeded for determinism (seed not specified)
    The 163-grain population depends on an unseeded RANSAC registration; re-running can change the population and shift reachability percentages by a few points (appendix A).
assumptions (6)
  • standard math Spherical geometry of cone–circle intersection underlying eq. (2)
    The beam on a cone of half-angle t and a plane normal at polar angle α have an angular separation ranging over [|α−t|, α+t]; the reachability annulus follows from this standard spherical-distance fact (§2.1).
  • standard math Two-beam condition holds when k̂·ĝ = ±sin θ_B (Bragg geometry)
    The sg=0 locus is the band edge, θ_B off the plane normal; the signed ± distinction is kept throughout (§2.1, §3).
  • domain assumption Dynamical Kikuchi/channeling simulation yields faithful relative intensities at arbitrary beam directions
    The Sweep step samples a dynamically simulated channeling pattern (eCHORD lineage, refs 21–23). Validated in §5 at a single orientation ([001] Si, ~7° tilt); transfer to arbitrary grain orientations in a polycrystal is assumed and untested.
  • domain assumption A grain's EBSD-measured orientation is a valid single orientation for the whole imaged region
    Internal lattice rotations of ~2° in deformed grains mean no single predicted condition holds across the grain; the paper states this limitation in §1 and §6.2.
  • domain assumption Rival reflections can be dropped by structure factor, and curated reflector tables suffice
    The clearance gate of eq. (4) requires the rival list; §6.2 states the implementation uses curated reflector tables without computed structure factors.
  • domain assumption Stage rotation is exactly about the specimen normal at fixed tilt, with known kinematic sense
    The cone model and the inverse stage kinematics (Range step) assume this; the stage sense had to be pinned empirically in the §5 validation.

how reviews work

0 comments
Cite this review

Pith. "Pith review of GRADAR: orientation-map-driven detection and ranking of grains for targeted two-beam electron channeling contrast imaging." pith.science (2026). https://pith.science/paper/YMMXXRTL

@misc{pith2026260802400,
  author       = {Pith},
  title        = {Pith review of: GRADAR: orientation-map-driven detection and ranking of grains for targeted two-beam electron channeling contrast imaging},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YMMXXRTL}},
  note         = {Machine review of arXiv:2608.02400}
}
abstract

Electron channeling contrast imaging (ECCI) resolves individual dislocations in bulk samples, but only when the imaged grain is held in a two-beam diffraction condition to well under half a degree. In a polycrystal it must be re-established grain by grain, and every published workflow we are aware of chooses the grain first and solves the stage for that orientation. This paper treats the inverse problem: nominate one reflection family and a stage envelope, and determine which grains of an EBSD-mapped polycrystal can reach that family's two-beam condition, a question posed in 2019 and open since. At fixed tilt $t$, stage rotation sweeps the incident beam around a cone of half-angle $t$ in each grain's crystal frame, and a family with Bragg angle $\theta_B$ is reachable exactly when one of its plane normals lies within $(t + \theta_B)$ of the specimen surface. On a measured 163-grain austenitic stainless steel map at 20 kV, {111} reachability rises from 38.7% at 7 deg tilt to 77.3% at 15 deg; {220} and {311} already reach 79.8% and 91.4% at 7 deg. Ranking survivors by predicted darkness alone is wrong: same-family candidates are equivalent with respect to their own band at exact Bragg incidence, and the darkest tend to lie closest to rival-band Bragg conditions. GRADAR therefore ranks darkest-clean, gating every candidate on a minimum clearance from all rivals, and returns a dial-ready stage move per selected grain. Because the beam moves only ~0.12 deg per degree of stage rotation at 7 deg tilt, an ordinary rotation stage sets the selected condition to better than 0.1 deg. The predicted sweep is checked against the AstroECP dataset's published silicon precession series: simulated and measured traces agree at r = 0.84, and the measured intensity is dark at all 16 predicted two-beam edges. Per-grain polycrystal validation is deferred to a companion study.

Figures

Figures reproduced from arXiv: 2608.02400 by the authors.

Figure 1
Figure 1. Rotational ECCI on the Kikuchi sphere: a dynamically simulated nickel reference pattern [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. The reachability construction. (a) At fixed tilt [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. The pipeline. Sweep simulates each grain’s channeling intensity and beam direction over [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Two-beam condition selection in autoECCI’s interactive targeting report, which suggests the stage tilt and rotation for the selected diffraction vector, on a simulated nickel channeling pattern near [110] (20 kV). Left: the simulated pattern with its geometrical band o…
Figure 5
Figure 5. Figure 5: Why darkest-first fails, schematically. Along the [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 6
Figure 6. Figure 6: Reachability on the measured 163-grain austenitic steel map at 20 kV, with the random [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]
Figure 7
Figure 7. Figure 7: The austenitic steel orientation map, IPF-Z coloured with a pattern-quality overlay [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]
Figure 8
Figure 8. Figure 8: Simulated sweep versus the measured Si precession series at [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

32 extracted references · 16 canonical work pages

  1. [1]

    Electron channeling contrast tomography (ECCT): dislocation tomography enabled by ECCI.Scripta Materialia, 277:117234, 2026

    Timmo Weidner, Romain Gautier, Antoine Guitton, and Alexandre Mussi. Electron channeling contrast tomography (ECCT): dislocation tomography enabled by ECCI.Scripta Materialia, 277:117234, 2026. doi: 10.1016/j.scriptamat.2026.117234

    arXiv 2026

  2. [2]

    Early stage strain localization at grain boundaries during fatigue studied using in situ electron channeling contrast imaging and high-resolution electron backscattered diffraction

    Yang Su and Josh Kacher. Early stage strain localization at grain boundaries during fatigue studied using in situ electron channeling contrast imaging and high-resolution electron backscattered diffraction. Scripta Materialia, 262:116647, 2025. doi: 10.1016/j.scriptamat.2025.116647

    arXiv 2025

  3. [3]

    Haroon Qaiser, Jessica White, David Wallis, and T

    M. Haroon Qaiser, Jessica White, David Wallis, and T. Ben Britton. Characterizing dislocation sub- structures in creep-deformed olivine using electron channeling contrast imaging.Journal of Geophysical Research: Solid Earth, 131(7):e2026JB034771, 2026. doi: 10.1029/2026JB034771

    work page doi:10.1029/2026jb034771 2026

  4. [4]

    Jacopo Frascaroli, Andrea Serafini, Fabiana Vento, Francesco Somaini, Nicolò Piluso, Andrea Severino, Cristiano Calabretta, Isabella Mica, and Davide Codegoni. Revealing threading dislocations in epitaxial GaN: a comparative study of electron channeling contrast imaging, KOH etch, and TEM characteriza- tion.Semiconductor Science and Technology, 41(2):0250...

    work page doi:10.1088/1361-6641/ae3edf 2026

  5. [5]

    Laura Monge-Bartolome, Paula Mouriño Miñambres, Alicia Peiro Codoñer, Miguel Sinusia Lozano, Zhao Yan, Ivan Garcia Vara, Thierry Baron, Qiang Li, and Víctor J. Gómez. Electron channeling contrast imaging for the characterization of dislocations in III–V thin films on silicon (001).physica status solidi (a), 223(2):e202500580, 2026. doi: 10.1002/pssa.202500580

    work page doi:10.1002/pssa.202500580 2026

  6. [6]

    Characterization of irradiation-induced dislocation loops and helium bubbles via electron channeling contrast imaging.Materialia, 33:101987, 2024

    Shangkun Shen, Yingxi Li, Liyu Hao, Xing Liu, Xuanpu Zhang, Shuangle Zhang, Jinlong Du, Jian Zhang, Kunjie Yang, Miao Song, and Engang Fu. Characterization of irradiation-induced dislocation loops and helium bubbles via electron channeling contrast imaging.Materialia, 33:101987, 2024. doi: 10.1016/j.mtla.2023.101987

    arXiv 2024

  7. [7]

    Dauphinétwininadeformedquartz: characterization by electron channelling contrast imaging and large-angle convergent-beam diffraction

    NobuyoshiMiyajima, DanielleSilvaSouza, andFlorianHeidelbach. Dauphinétwininadeformedquartz: characterization by electron channelling contrast imaging and large-angle convergent-beam diffraction. European Journal of Mineralogy, 36(5):709–719, 2024. doi: 10.5194/ejm-36-709-2024

    work page doi:10.5194/ejm-36-709-2024 2024

  8. [8]

    Theory and application of electron channelling con- trast imaging under controlled diffraction conditions.Acta Materialia, 75:20–50, 2014

    Stefan Zaefferer and Nahid-Nora Elhami. Theory and application of electron channelling con- trast imaging under controlled diffraction conditions.Acta Materialia, 75:20–50, 2014. doi: 10.1016/j.actamat.2014.04.018. 15

    work page doi:10.1016/j.actamat.2014.04.018 2014

Show all 32 references
  1. [9]

    Haroon Qaiser, Lukas Berners, Robin J

    M. Haroon Qaiser, Lukas Berners, Robin J. Scales, Tianbi Zhang, Martin Heller, Jiří Dluhoš, Sandra Korte-Kerzel, and T. Ben Britton. AstroECP: towards more practical electron channeling contrast imaging.Journal of Applied Crystallography, 59(2):530–551, 2026. doi: 10.1107/S160...

    2026 doi

  2. [10]

    Rotational-electron channeling contrast imaging analysis of dis- location structure in fatigued copper single crystal.Scripta Materialia, 162:103–107, 2019

    Gabriel L’hôte, Clément Lafond, Philippe Steyer, Stéphanie Deschanel, Thierry Douillard, Cyril Langlois, and Sophie Cazottes. Rotational-electron channeling contrast imaging analysis of dis- location structure in fatigued copper single crystal.Scripta Materialia, 162:103–107, ...

    2019 doi

  3. [11]

    Coupling of electron channeling with EBSD: toward the quantitative characterization of deformation structures in the SEM.JOM, 65(9):1229–1236,

    Ivan Gutierrez-Urrutia, Stefan Zaefferer, and Dierk Raabe. Coupling of electron channeling with EBSD: toward the quantitative characterization of deformation structures in the SEM.JOM, 65(9):1229–1236,

  4. [13]

    Takashige Mori, Takafumi Amino, Chie Yokoyama, Shunsuke Taniguchi, Takayuki Yonezawa, and Akira Taniyama. Observation and quantitative analysis of dislocations in steel using electron channeling contrastimagingmethodwithprecisecontrolofelectronbeamincidentdirection.Microscopy,...

    2024 doi

  5. [14]

    Luda Wang, Benoit Beausir, Yudong Zhang, Claude Esling, Xiang Zhao, Hai-Le Yan, and Liang Zuo. A software-assisted crystallographic approach for achieving specific beam orientations for transmis- sion electron microscopy characterization.Journal of Applied Crystallography, 59(...

    2026 doi

  6. [15]

    ALPHABETA: a dedicated open-source tool for calculating TEM stage tilt angles.Journal of Microscopy, 273(3):189–198, 2019

    Niels Cautaerts, Rémi Delville, and Dominique Schryvers. ALPHABETA: a dedicated open-source tool for calculating TEM stage tilt angles.Journal of Microscopy, 273(3):189–198, 2019. doi: 10.1111/jmi.12774

    2019 doi

  7. [16]

    doi: 10.1107/S1600576720000801

    Rui-Xun Xie and Wen-Zheng Zhang.τompas: a free and integrated tool for online crystallographic analysis in transmission electron microscopy.Journal of Applied Crystallography, 53(2):561–568, 2020. doi: 10.1107/S1600576720000801

    2020 doi

  8. [17]

    crystalAligner: a computer program to align crystal directions in a scanning electron microscope by global optimization.Journal of Applied Crystallography, 53(1):282–293, 2020

    Frank Niessen. crystalAligner: a computer program to align crystal directions in a scanning electron microscope by global optimization.Journal of Applied Crystallography, 53(1):282–293, 2020. doi: 10.1107/S1600576719017345

    2020 doi

  9. [18]

    Towards large scale orientation mapping using the eCHORD method.Ultramicroscopy, 208:112854, 2020

    Clément Lafond, Thierry Douillard, Sophie Cazottes, Marc De Graef, Philippe Steyer, and Cyril Langlois. Towards large scale orientation mapping using the eCHORD method.Ultramicroscopy, 208:112854, 2020. doi: 10.1016/j.ultramic.2019.112854

    2020

  10. [19]

    eCHORD crystalline orientation maps: channeling contrast at interfaces.BIO Web of Conferences, 129:07031,

    Cyril Langlois, Gabriel L’Hôte, Thierry Douillard, Matthieu Bugnet, and Claire Maurice. eCHORD crystalline orientation maps: channeling contrast at interfaces.BIO Web of Conferences, 129:07031,

  11. [20]

    Enhancing eCHORD orientation mapping by means of a derivative approach.Microscopy and Microanalysis, 31(3):ozaf054, 2025

    Gabriel L’Hôte, Thierry Douillard, Claire Maurice, Matthieu Bugnet, Romain Haeffele, Sabrina Marcelin, Bernard Normand, and Cyril Langlois. Enhancing eCHORD orientation mapping by means of a derivative approach.Microscopy and Microanalysis, 31(3):ozaf054, 2025. doi: 10.1093/ma...

    2025 doi

  12. [21]

    Electron CHanneling ORientation Determination (eCHORD): an original approach to crystalline orientation mapping.Ultramicroscopy, 186:146–149, 2018

    Clément Lafond, Thierry Douillard, Sophie Cazottes, Philippe Steyer, and Cyril Langlois. Electron CHanneling ORientation Determination (eCHORD): an original approach to crystalline orientation mapping.Ultramicroscopy, 186:146–149, 2018. doi: 10.1016/j.ultramic.2017.12.019

    2018 doi

  13. [22]

    Ben Britton

    Tianbi Zhang, Raynald Gauvin, Aimo Winkelmann, and T. Ben Britton. Dynamical simulation of on-axis transmission Kikuchi and spot diffraction patterns, based on accurate diffraction geometry calibration.Journal of Microscopy, 303(2):139–153, 2026. doi: 10.1111/jmi.70119

    2026 doi

  14. [23]

    Wright, Matthew M

    William Lenthe, Stuart I. Wright, Matthew M. Nowell, and Rene de Kloe. Fast Kikuchi spheres for forward model EBSD indexing.Microscopy and Microanalysis, 31(Supplement 1):ozaf048.280, 2025. Conference abstract; doi: 10.1093/mam/ozaf048.280. 16

    2025 doi

  15. [24]

    Woodcock, Tina Bergh, Eric Prestat, Austin Gerlt, Andreas V

    Håkon Wiik Ånes, Lars Andreas Hastad Lervik, Ole Natlandsmyr, Thomas G. Woodcock, Tina Bergh, Eric Prestat, Austin Gerlt, Andreas V. Bugten, Erlend Mikkelsen Østvold, Zhou Xu, Carter Francis, Magnus Nord, and Tijmen Vermeij. pyxem/kikuchipy: kikuchipy 0.13.0. Zenodo, 2026. Ope...

    2026

  16. [25]

    Demo datasets used by the openECCI python library

    Zhou Xu, Håkon Wiik Ånes, Sergey Gorelick, Xiya Fang, and Peter Miller. Demo datasets used by the openECCI python library. Zenodo, 2024. CC BY 4.0; doi: 10.5281/zenodo.11169052; record: https://zenodo.org/records/11169052

    2024

  17. [26]

    Haroon Qaiser, Lukas Berners, Robin J

    M. Haroon Qaiser, Lukas Berners, Robin J. Scales, Tianbi Zhang, Martin Heller, Jiří Dluhoš, Sandra Korte-Kerzel, and T. Ben Britton. Data bundle for: AstroECP – towards more practical electron channeling contrast imaging. Zenodo, 2026. doi: 10.5281/zenodo.15778499; record:http...

    2026

  18. [27]

    Tong, Jim Hickey, Alex Foden, and Angus J

    Thomas Benjamin Britton, Vivian S. Tong, Jim Hickey, Alex Foden, and Angus J. Wilkinson. As- troEBSD: exploring new space in pattern indexing with methods launched from an astronomical ap- proach.Journal of Applied Crystallography, 51(6):1525–1534, 2018. doi: 10.1107/S1600576718010373

    2018 doi

  19. [28]

    Bedell, Kunal Mukherjee, John A

    Stephen W. Bedell, Kunal Mukherjee, John A. Ott, Devendra K. Sadana, and Brent A. Wacaser. Automatic alignment for high throughput electron channeling contrast imaging. US Patent 9,859,091 B1, 2018. Granted 2 January 2018; assignee International Business Machines Corporation;h...

    2018

  20. [29]

    Bedell, Kunal Mukherjee, John A

    Stephen W. Bedell, Kunal Mukherjee, John A. Ott, Devendra K. Sadana, and Brent A. Wacaser. Elec- tronchannelingpatternacquisitionfromsmallcrystallineareas. USPatent11,003,942B2, 2021. Granted 11 May 2021; assignee International Business Machines Corporation;https://patents.goo...

    2021

  21. [30]

    della Ventura, James D

    Nicolò M. della Ventura, James D. Lamb, William C. Lenthe, McLean P. Echlin, Julia T. Pürstl, Emily S. Trageser, Alejandro M. Quevedo, Matthew R. Begley, Tresa M. Pollock, Daniel S. Gianola, and Marc De Graef. Orientation-adaptive virtual imaging of defects using EBSD.Ultramic...

    2025

  22. [31]

    Ben Britton, M

    T. Ben Britton, M. Haroon Qaiser, and Ruth M. Birch. Channeling-in channeling-out revisited: selected area electron channeling and electron backscatter diffraction.Ultramicroscopy, page 114384, 2026. doi: 10.1016/j.ultramic.2026.114384. 17

    2026

  23. [2013]

    doi: 10.1007/s11837-013-0678-0

    doi

  24. [2024]

    doi: 10.1051/bioconf/202412907031

Pith tools

Reviewed August 4, 2026 · model on record in the stance chip above.