Vision64 map

Manufactured by Bruker

Sourced in Germany, United States

The Vision64 Map is a versatile laboratory equipment designed for high-performance imaging and analysis. This product offers advanced optical capabilities to support a wide range of scientific applications.

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Lab products found in correlation

Inca energy 300, by Oxford Instruments (1 mentions) Contour gt k1 optical profiler, by Bruker (1 mentions) Color eye 7000a, by X-Rite (1 mentions)

Close spelling variants of this product

Vision64 (29 citations) Vision64 Map software (2 citations)

3 protocols using vision64 map

Microstructural and Surface Roughness Analysis of Laser-Treated Samples

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The microstructural features of polished and treated samples were investigated by scanning electron microscopy (FE-SEM, Carl Zeiss Sigma NTS Gmbh, Oberkochen, Germany) and energy dispersive X-ray spectroscopy (EDS, INCA Energy 300, Oxford instruments, Abingdon, UK).
The roughness characterization of the as-machined and laser-treated surfaces was performed with a ContourGT-K 3D non-contact profilometer (Bruker, Germany) on areas of 6 × 6 mm² in each quadrant of the discs, and the topography data were analyzed using commercial software (Vision64 Map). The evaluation of texture parameters was carried out in terms of linear and areal field parameters according to the ISO 4287 standard. Measurements of mean linear surface roughness (R_a) and distance between the highest asperity, peak, or summit and the lowest valley (R_t) were performed parallel and perpendicular to the laser path, while mean areal surface roughness (S_a) was evaluated on the whole investigated area.

Sani E., Sciti D., Failla S., Melandri C., Bellucci A., Orlando S, & Trucchi D.M. (2023). Multi-Scale Femtosecond-Laser Texturing for Photothermal Efficiency Enhancement on Solar Absorbers Based on TaB2 Ceramics. Nanomaterials, 13(10), 1692.

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Evaluating Surface Roughness and Color Change

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All specimens for the three groups were subjected to baseline surface roughness and color change measurements before aging. Surface roughness (R_a, µm) readings were recorded at three points for each specimen using an Optical Profiler (Contour GT-K1 optical profiler; Bruker Nano, AZ, USA). All three scans were performed on each specimen at 20× magnification. Data analysis of the acquired images was then done using Vision64 software (Vision64 Map; Bruker Nano) (Fig. 1).Fig. 1

Images represent surface roughness of the ceramic materials. A: EC before thermocycing. B: EC after thermocycling. C. EP before thermocycing. D: EP after thermocycling. E. LP before thermocycing. F: LP after thermocycling.

Measurements of color change were performed using a spectrophotometer (Color-Eye 7000A; X-rite, Grand Rapids, Michigan, USA). Following the manufacturer’s directions, black and white ceramic tiles were employed to calibrate the spectrophotometer. The color values were secured using the CIE L*a*b* color system, where the measurements of the color variables (L*, a*, b*) were performed on each side and at the specimen’s center.

Al-Thobity A.M., AlOtaibi A.M., Alhumaidan A.E., Aldossary A.A., Siddiqui I.A., Helal M.A, & Alsalman A. (2022). Impact of thermocycling on surface roughness, microhardness and optical properties of three different lithium disilicate ceramics. The Saudi Dental Journal, 34(7), 589-595.

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Profilometric Analysis of Scaffold Morphology

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Surface morphology was assessed using a Countour GT-K1 3D optical profilometer (Veeco, USA). Briefly, scaffolds (n=2 per type) were placed on glass coverslips and fixed with ethanol to ensure a near flat surface. They were then pre-conditioned in supplemented culture media overnight and dehydrated in a series of ethanol solutions prior to imaging. Samples were imaged in vertical scanning interferometry mode. A total of 10 micrographs (66 μm × 87 μm) were taken per sample at different fields of view, with an average of five measurements per image. Analysis of the surface roughness (arithmetical mean surface height (Sa) and root mean square surface height (Sq)) based on 3D profile ordinates was performed with the Vision64 Map ™ (Bruker, USA) software.

Magaz A., Spencer B.F., Hardy J.G., Li X., Gough J.E, & Blaker J.J. (2020). Modulation of Neuronal Cell Affinity on PEDOT-PSS Nonwoven Silk Scaffolds for Neural Tissue Engineering. ACS biomaterials science & engineering, 6(12).

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