- Thème : Spectroscopie des nanomatériaux

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Accueil > La Recherche > Axes & Equipes > Bio Nano Imagerie > Equipe : Spectroscopie et Imagerie RMN > Thème : Spectroscopie des nanomatériaux

Thème : Spectroscopie des nanomatériaux

Présentation

Historically, we have successfully used high resolution solid state NMR to investigate the electronic, magnetic and dynamical properties of fullerenes, single-walled carbon nanotubes (SWNT) and some of their derivatives like functionalized, intercalated, hydrogenated, encapsulated SWNTs and composite systems, in collaboration with several Materials Science groups. For this purpose, we have developed isotopical engineering for the synthesis of SWNTS and a new magnetic purification method. For instance, our findings in peapods demonstrated, for the first time, the existence of strong magnetic shielding created by electronic ring currents circulating in the side walls of the nanotubes. In addition, we reported experimental evidences using 13C and 1H NMR that controlled chemical reactions as hydrogenation at the interior space of SWNT is, indeed, feasible at elevated pressure and temperature. We demonstrated that the rotational dynamics of the encapsulated C60Hx molecules are clearly hindered. Hence, SWNT have been shown to be potential ultra clean nano reactors and gas transport systems. Our successful experiments on encapsulated systems inside SWNT open completely new roads to understand and control confined chemical reactions at the nano scale.

Collaborations : D.E. Luzzi (MSE Philadelphia), A. Zettl (UCB, Berkeley), M. Mehring (Stuttgart), T. Wagberg (Umea), G. Bidan (CEA, Grenoble)

Fundings : ACI-Nano NACEP (2004-2006), Molecular Foundry Berkeley (2005-2007), Région Languedoc-Roussillon (2006)

Toutes les productions

Dernières publications

Micro‐CT and high‐field MRI for studying very early post‐mortem human fetal anatomy at 8 weeks of gestation

Auteur(s): Lamouroux Audrey, Cardoso Maïda, Bottero Célia, Gallo Mathieu, Duraes Martha, Salerno Jennifer, Bertrand Martin, Rigau Valérie, Fuchs Florent, Mousty Eve, Genevieve David, Subsol Gérard, Goze-Bac C., Captier Guillaume

(Article) Publié: Prenatal Diagnosis, vol. 44 p.3-14 (2024)

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure

Auteur(s): Fernandez Romain, Le Cunff Loïc, Mérigeaud Samuel, Verdeil Jean‐Luc, Perry Julie, Larignon Philippe, Spilmont Anne-Sophie, Chatelet Philippe, Cardoso Maïda, Goze-Bac C., Moisy Cédric

(Article) Publié: Scientific Reports, vol. 14 p.5033 (2024)

Ref HAL: hal-04501077_v1
PMID 38424155
DOI: 10.1038/s41598-024-55186-3
Exporter : BibTex | endNote
Résumé:

Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for example, to assess plant health and quality and monitor physiological traits or diseases. However, detecting functional and degraded plant tissues in-vivo without harming the plant is extremely challenging. New solutions are needed in ligneous and perennial species, for which the sustainability of plantations is crucial. To tackle this challenge, we developed a novel approach based on multimodal 3D imaging and artificial intelligence-based image processing that allowed a non-destructive diagnosis of inner tissues in living plants. The method was successfully applied to the grapevine ( Vitis vinifera L.). Vineyard’s sustainability is threatened by trunk diseases, while the sanitary status of vines cannot be ascertained without injuring the plants. By combining MRI and X-ray CT 3D imaging with an automatic voxel classification, we could discriminate intact, degraded, and white rot tissues with a mean global accuracy of over 91%. Each imaging modality contribution to tissue detection was evaluated, and we identified quantitative structural and physiological markers characterizing wood degradation steps. The combined study of inner tissue distribution versus external foliar symptom history demonstrated that white rot and intact tissue contents are key measurements in evaluating vines’ sanitary status. We finally proposed a model for an accurate trunk disease diagnosis in grapevine. This work opens new routes for precision agriculture and in-situ monitoring of tissue quality and plant health across plant species.

Commentaires: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. The extension of the Trainable Segmentation plugin is open-source, and available as a fork of Trainable Segmentation on GitHub https://github.com/Rocsg/Trainable_Segmentation/tree/Hyperweka.

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