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Cypher VRS1250 Video-Rate AFM

The Cypher VRS1250 is twice as fast as the first-generation Cypher VRS, scanning at up to 1250 lines/second. This enables either higher temporal resolution with frame rates up to 45 frames/second or increased spatial resolution by collecting more image pixels at lower frame rates. Combined with ultra-stable imaging, an easy-to-use fully sealed sample cell with perfusion capability, and a full range of modes and accessories, the Cypher VRS1250 is ready to help you achieve your most ambitious research goals.

  • Designed for both ultra-high speed and ultra-high resolution

  • Stable imaging allows dynamic events to be captured without drift or parameter adjustments

  • Ease of use features make setup and imaging simple

    • Includes all the added flexibility and capabilities of the Cypher ES research AFM


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    Cypher VRS1250 Brochure
    Cypher Family Brochure

    Designed for ultra-high speed and spatial resolution

    • Select the ideal balance between imaging speed and imaging resolution for your experiments
    • Cypher AFM’s easily and consistently achieve higher resolution than other AFM’s
    • The Cypher VRS1250 enables true video-rate imaging at rates up to 45 frames/second

    Stable imaging keeps the “focus” on your sample

    • The Cypher’s advanced design balances thermal expansion to virtually eliminate thermal drift
    • blueDrive photothermal excitation technology keeps imaging stable over long durations
    • Fully sealed sample cell keep imaging stable such that even delicate biomolecules can be observed without damage

    Ease of use features make it easier to get great results

    • The Cypher VRS1250 is designed with the same ease-of-use features as other Cypher AFM’s
    • Motorized laser and detector alignment and simple probe loading make setup fast and easy
    • A fully sealed sample cell eliminates worries over leakage
    • Software includes features to easily process and export video-rate AFM movies for presentations and publications.

    All the flexibility and capabilities of Cypher AFM's

    • The Cypher VRS1250 supports all the functionality and associated benefits of the Cypher ES environmental AFM
    • Options include sample heating and cooling and a complete range of operating modes.
    • Cypher VRS 1250 is much more than just a video-rate AFM. The platform is the ideal AFM for interdisciplinary research groups and shared imaging facilities.

    Included Operating Modes

    Contact mode
    DART PFM
    Dual AC
    Dual AC Resonance Tracking (DART)
    Electrostatic Force Microscopy (EFM)
    Force curves
    Force Mapping Mode (force volume)
    Force modulation
    Frequency modulation
    Kelvin Probe Force Microscopy (KPFM)
    Lateral Force Mode (LFM)
    Loss tangent imaging
    Magnetic Force Microscopy (MFM)
    Nanolithography
    Nanomanipulation
    Phase imaging
    Piezoresponse Force Microscopy (PFM)
    Switching spectroscopy PFM
    Tapping mode (AC mode)
    Tapping mode with digital Q control
    Vector PFM

    Included because Cypher VRS comes with blueDrive

    AM-FM Viscoelastic Mapping Mode
    Contact Resonance Viscoelastic Mapping Mode

    Optional Operating Modes

    Conductive AFM (CAFM) with ORCA™ and Eclipse™ Mode
    Current mapping with Fast Force Mapping
    Electrochemical Strain Microscopy (ESM)
    Fast Force Mapping Mode
    High voltage PFM
    Nanoscale Time Dependent Dielectric Breakdown (nanoTDDB)
    Scanning Capacitance Microscopy (SCM)
    Scanning Microwave Impedance Microscopy (sMIM)
    Scanning Tunneling Microscopy (STM)

    Kalinin, S. V., Zhang, S., Valleti, M., Pyles, H., Baker, D., De Yoreo, J. J., & Ziatdinov, M. (2021). Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations. ACS nano. https://doi.org/10.1021/acsnano.0c08914

    Ziatdinov, M., Zhang, S., Dollar, O., Pfaendtner, J., Mundy, C. J., Li, X., ... & Kalinin, S. V. (2020). Quantifying the dynamics of protein self-organization using deep learning analysis of atomic force microscopy data. Nano Letters, 21(1), 158-165. https://dx.doi.org/10.1021/acs.nanolett.0c03447

    Chen, J., Zhu, E., Liu, J., Zhang, S., Lin, Z., Duan, X., ... & De Yoreo, J. J. (2018). Building two-dimensional materials one row at a time: Avoiding the nucleation barrier. Science, 362(6419), 1135-1139. https://doi.org/10.1126/science.aau4146

    Mao, X., Li, K., Liu, M., Wang, X., Zhao, T., An, B., ... & Wang, L. (2019). Directing curli polymerization with DNA origami nucleators. Nature communications, 10(1), 1-10. https://doi.org/10.1038/s41467-019-09369-6

    Sigdel, K. P., Wilt, L. A., Marsh, B. P., Roberts, A. G., & King, G. M. (2018). The conformation and dynamics of P-glycoprotein in a lipid bilayer investigated by atomic force microscopy. Biochemical pharmacology, 156, 302-311. https://doi.org/10.1016/j.bcp.2018.08.017

    Zhu, H., Wang, X., Cui, Y., Cai, J., Tian, F., Wang, J., & Qiu, H. (2019). Blooming of Block Copolymer Micelles into Complex Nanostructures on a Surface. Macromolecules, 52(9), 3479-3485. https://doi.org/10.1021/acs.macromol.9b00197

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