Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

Lim, R.E.; Shang, S.-L.; Chuang, C.; Phan, T.Q.; Liu, Z.-K.; Pagan, D.C.

doi:10.1107/S2053273325000403

Acta Crystallographica Section A
Acta Crystallographica
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Figure 6
Representative fields from the thermomechanical simulations (P = 120 W, v = 0.05 m s⁻¹ and spot diameter of 100 µm) as the laser is passing overhead: (a) T, (c) $[\varepsilon^{\rm T}]$ , (e) $[\varepsilon^{\rm E}_{xx}]$ and (g) $[\varepsilon^{\rm E}_{zz}]$ . Representative fields from the same laser parameter simulation after cooling: (b) T, (d) $[\varepsilon^{\rm T}]$ , (f) $[\varepsilon^{\rm E}_{xx}]$ and (h) $[\varepsilon^{\rm E}_{zz}]$ .

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ISSN: 2053-2733

Volume 81| Part 2| March 2025| Pages 137-150

https://doi.org/10.1107/S2053273325000403

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