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Enregistrement W4412910947 · doi:10.1093/mam/ozaf048.1153

Hydrophilization and Activation of Carbon Coated TEM Grids Using a Light Spectrum Device

2025· article· en· W4412910947 sur OpenAlexaff
Daniela Vieira, Mojtaba Safari, Hooman Hosseinkhannazer, Emad Shahnam, Jared Lapkovsky

Notice bibliographique

RevueMicroscopy and Microanalysis · 2025
Typearticle
Langueen
DomaineEngineering
ThématiqueElectrohydrodynamics and Fluid Dynamics
Établissements canadiensNorQuest CollegeUniversité du Québec à Montréal
Organismes subventionnairesnon disponible
Mots-clésHydrophilizationMaterials scienceSpectrum (functional analysis)Carbon fibersOptoelectronicsComposite materialPhysics

Résumé

récupéré en direct d'OpenAlex

Transmission Electron Microscopy (TEM) is at the cutting edge of nanoscale imaging, enabling the visualization of structures with atomic-level detail [1]. The accuracy and quality of TEM analysis is strongly dependent on the specimens deposition onto the TEM grid [2]. The deposition must be performed well to ensure efficacy and high-resolution images [3]. For TEM characterization of organic and inorganic nanoparticles the samples are typically prepared following a manual drop-casting procedure. In this method, the nanoparticles are dispersed by ultrasonication while still in solution, dropped onto the TEM grid, excess liquid blotted away, and then the grid left to air-dry [4,5]. However, during the air-drying step the nanoparticles are likely to agglomerate due to the solvent’s surface tension, limiting ability to characterize individual particles. To avoid having agglomerated particles, glow discharge is commonly used to pre-treat the carbon coated TEM grids prior to deposition, converting the film from hydrophobic to hydrophilic [6,7]. The process of glow discharge involves the TEM grids being exposed to a plasma generated by high voltage while under vacuum. The plasma contains ions and radicals, which react with the carbon surface to reduce its hydrophobicity [6-7]. There are many commercial glow discharge systems available for treating TEM grids [8,9]; however, these systems are limited in that they can be quite large and require a vacuum system, demanding frequent maintenance, are over 20 kg, and they cannot be easily relocated to different places. The glow discharge is usually used with a narrow process window, with just a few seconds of extra time the end user can easily damage the grid. As an alternative to glow discharge, the hydrophilicity of TEM grids can be increased by another method light-based surface treatment using a wide spectrum of light. The UltiFlow (Norcada, Alberta, Canada) is a bench-top instrument that uses a light spectrum to activate and hydrophilize the surface[10]. The UltiFlow can consistently prepare TEM grids that are hydrophilic in a few minutes, with this state lasting for up to one hour after each cycle[10]. In addition, the UltiFlow device does not require vacuum, weighs under 2kg, and requires no maintenance. In this work, we optimized the light treatment methodology for hydrophobic to hydrophilic conversion of carbon coated TEM grids and compared the light treatment method’s performance to that of glow discharge. Low voltage electron microscopy (LVEM) (LVEM 25E, Delong Instruments) was used to characterize and quantify the performance and effectiveness of the pre-treatment method. LVEM allows fast imaging with high resolution, ideal for nanoparticle characterization. The integrity of the TEM grid’s carbon film after light treatment along with the distribution and homogeneity of the deposited particles were studied by LVEM. Images were systematically acquired at an accelerating voltage of 25 kV from predefined fixed areas of the TEM grids using the microscope’s software movement panel (Figure 1). The contact angle (a common technique to qualify hydrophobicity) of untreated and light treated grids was measured using ImageJ software after dropping 10 µL of water on the grids. Contact angles lower than 90° are expected for hydrophilic surfaces. The light treatment method was first optimized by varying the exposure time (1, 5 and 10 minutes) and power intensity (30%, 50% and 100%) of the UltiFlow. The contact angles showed no significant difference between untreated (103.0°±1.4), 1 min/100% (103.8°±1.4) and 5min/50% (106.0°±2.2) UltiFlow treated grids. A slight difference was noticed in 5 min/100% (95.0°±2.8) and better results were achieved at 10 min/30% (72.8°±4.2) UltiFlow treated grids (Figure 2). Integrity of the grids was confirmed by the LVEM image data (Figure 3). Indications of carbon film damage was observed in higher %power (100%) and in higher time applied (10 minutes). For example, 10 minutes/100% power was strong enough to visually damage the carbon film on the grids (Figure 3). It was found that treatment for 5 minutes at 50% power is the optimized setting for the UltiFlow device for most application cases. The performance of UV pre-treatment was then compared to the glow discharge method and to untreated TEM grids. Particle distribution and homogeneity was studied with different nanoparticle species. Gold nanoparticles (AuNPs), polymer particles and carbon nanotubes (CNTs) were dispersed in an aqueous solution, ultrasonicated for 15 minutes, then deposited in parallel by drop-casting onto TEM grids that have either received no pretreatment, or been pre-treated with either UV or plasma. All particles were deposited within 30 minutes of pre-treatment. Overall, for grids treated by UV with the UltiFlow device, particles were found to be well distributed, and less particle agglomeration was noticed as compared to imaging done on grids without any prior treatment (Figure 4). Specifically, for AuNPs, similar result was noticed for grids treated by UV as compared to those that received glow discharge treatment, where particles were well dispersed and less agglomerated. For CNTs, no significant difference was observed within the untreated, UV treated and glow discharge treated grids, probably due to the known high surface energy and surface area of CNTs[11]. UV treated grids were found to be even more efficient for the dispersion of polymer particles, showing a more homogeneous distribution when compared to glow discharge treated grids. In conclusion, the light-based treatment, as provided by the UltiFlow device, is confirmed as a more suitable alternative to glow discharge for hydrophobic to hydrophilic conversion of carbon coated TEM grids (Table 1). By using light spectrum technology along with a controlled heat around the TEM grids, particle agglomeration was avoided, and effective particle characterization was easily achieved. LVEM showed as a comprehensive imaging technique for the characterization of various types of nanoparticles. The combination of compact UltiFlow system and the benchtop and compact LVEM electron microscopes showed as a space saving, cost effective, fast and reliable setup for nanoparticles characterization. LVEM 25E instrument (Delong Instruments) with its movement panel for precise TEM-grid positioning. Qualitative contact angle measurements of untreated grids and grids treated with UltiFlow (Norcada). Integrity of TEM grids assessed by LVEM after light treatment. Higher percentages and longer exposure times damaged the carbon film LVEM images showing the distribution of AuNPs, polymer, and CNTs on untreated, light-treated, and glow discharge-treated TEM grids. Comparison of UltiFlow and Glow discharge equipment Comparison of UltiFlow and Glow discharge equipment

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,004
Tête enseignante GPT0,218
Écart entre enseignants0,214 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentnon

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