Photothermal depth profiling: Comparison between genetic algorithms and thermal wave backscattering (abstract)
Notice bibliographique
Résumé
Photothermal depth profiling has been the subject of many papers in the last years. Inverse problems on different kinds of materials have been identified, classified, and solved. A first classification has been done according to the type of depth profile: the physical quantity to be reconstructed is the optical absorption in the problems of type I, the thermal effusivity for type II, and both of them for type III. Another classification may be done depending on the time scale of the pump beam heating (frequency scan, time scan), or on its geometrical symmetry (one- or three-dimensional). In this work we want to discuss two different approaches, the genetic algorithms (GA) [R. Li Voti, C. Melchiorri, C. Sibilia, and M. Bertolotti, Anal. Sci. 17, 410 (2001); R. Li Voti, Proceedings, IV Int. Workshop on Advances in Signal Processing for Non-Destructive Evaluation of Materials, Quebec, August 2001] and the thermal wave backscattering (TWBS) [R. Li Voti, G. L. Liakhou, S. Paoloni, C. Sibilia, and M. Bertolotti, Anal. Sci. 17, 414 (2001); J. C. Krapez and R. Li Voti, Anal. Sci. 17, 417 (2001)], showing their performances and limits of validity for several kinds of photothermal depth profiling problems: The two approaches are based on different mechanisms and exhibit obviously different features. GA may be implemented on the exact heat diffusion equation as follows: one chromosome is associated to each profile. The genetic evolution of the chromosome allows one to find better and better profiles, eventually converging towards the solution of the inverse problem. The main advantage is that GA may be applied to any arbitrary profile, but several disadvantages exist; for example, the complexity of the algorithm, the slow convergence, and consequently the computer time consumed. On the contrary, TWBS uses a simplified theoretical model of heat diffusion in inhomogeneous materials. According to such a model, the photothermal signal depends linearly on the thermal effusivity inhomogeneities, which may be detected because they act as backscattering centers for the heat flux. The physical problem is reduced to the inversion of a algebraic linear system. The advantage is that TWBS allows excellent reconstructions, but only within the limits of validity of the approximate model, which include any slowly varying profile. Recently we have tested the perfomance of both TWBS and GA on linear conductivity profiles. In other words, we have done the numerical simulations of the photothermal measurements coming from a film over a substrate, where the conductivity in the film changes linearly from k1 at the surface, to k2 at the substrate. TWBS and GA have been used to reconstruct the original profiles. If the conductivity mismatch ranges as 0.2<k1/k2<5, the error averaged over the whole profile is lower than 1% for TWBS, and lower than 2% for GA. However, in the case of a stronger conductivity mismatch GA exhibits better performances. These results will be widely discussed in a publication in the near future.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».