How David C. Joy Contributed to My Research in Electron Microscopy
Notice bibliographique
Résumé
In the lines of a previous paper [1], this contribution will describe the strong influence that David C. Joy had in my research in electron microscopy. As a graduate student, in 1985, I developed my first Monte Carlo program following a paper by David Joy et al. [2] that describes the effect of Fast Secondary Electrons [FSE] on x-ray generation. Their simulations showed that FSE can generate a significant fraction of the x-rays for energy lines below 1 keV. My Monte Carlo simulations showed that FSE can make Cliff-Lorimer K factors composition dependant when one energy line is below 1 keV and the other above [3]. I met David Joy the first time at the 1988 EMSA conference of Milwaukee where I asked him several technical questions. He was very nice to answer to a young student. Later, he accepted to be the external evaluator of my Ph. D. thesis that I defended in July 1990. After graduation, I started to work as Assistant Professor at University de Sherbrooke and we started to collaborate. I visited him several times in Knoxville. At one of those visits, he gave me his computed values of the Mott elastic cross sections and this eventually led to the creation of the program CASINO that was released in 1996 [4]. The help of David Joy must be credited in the development of CASINO. Figure [1] shows plot of electron trajectories in bulk Silicon at 1, 5 and 10 keV simulated with CASINO. These simulations followed those made by David Joy [5] for C. As it can be seen, in bulk Si, the electron range goes from 1 μm at 10 keV to 10 nm at 1 keV. David Joy [5] promoted low voltage SEM to improve spatial resolution. Since getting TEM was nearly impossible at that time, I jumped to this idea and we predicted that 10 nm spherical MnS inclusions in steel can be imaged at 5 keV with a 10 nm probe size using CASINO [6]. Figure [2] shows a 3 keV BSE picture of an bulk Aluminum alloy AA2199 taken with the Hitachi SU-8230. T1 plates (AlLiCu) of 2 – 4 nm width, δ′ phases (Al3Li) and β phases (Al3Zr) of 20 nm of radius are clearly visible, demonstrating the validity of the predictions made by Monte Carlo simulations in 1995. Low voltage SEM competes with TEM without having to make thin foils. While I visited David Joy the first time in Knoxville, in March 1991, he told me that STEM in the SEM will work because with the new cold field emitters and no lens below the sample, the chromatic aberration will be minimal, and the spatial resolution of this imaging mode will be almost as good as conventional TEM. He made many STEM instrumental contributions with the Hitachi S-5500. I followed David Joy idea with the Hitachi SU-8000 and SU-8230 for STEM at 30 keV, with Nicolas Brodusch and Hendrix Demers [7]. In 2017, I acquired the SU-9000 from Hitachi that has a resolution of 1,6 Å in Bright Field STEM at 30 keV and with the first EELS detector out of the Naka factory. Figure [3] shows a Li EELS jump ratio map of the AA 2199 alloy acquired at 30 keV. T1 plates of 2 nm and δ′ phases of 20 nm are clearly visible. Each time I see the results of the SU-9000, the remember what David Joy told me in 1991. Monte Carlo simulations of electron trajectories in bulk Silicon at 1, 5 and 10 keV simulated with CASINO. CASINO is available for free at www.mermg.com. Aluminum alloy AA 2199 imaged at 3 keV from a bulk specimen with the Hitachi SU-8230. Picture taken by Nicolas Brodusch. Li jump ratio EELS map of an Aluminum alloy AA 2199 acquired at 30 keV with the Hitachi SU-9000. Image acquired by Nicolas Brodusch.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,007 |
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 source (Gemma direct ou Codex distillé), 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 ».